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Welcome to ClickAI Radio, where you'll learn the secrets for transforming your business leveraging Artificial Intelligence. Join Grant on his journey through the AI maze as together we unravel the multiple technologies and identify those things that will benefit your business and the items you can ignore! As a gift to listeners, Grant is offering his AI for business ebook for free. Go to ClickAIRadio.com and download yours today. Remember to subscribe and leave feedback! Visit ClickAIRadio.com now...
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CAIR 78: High Impact AI RESULTS For Your Business, Now!
01/13/2023
CAIR 78: High Impact AI RESULTS For Your Business, Now!
What are the main challenges that I need to solve as a company trying to apply AI to help my business? In this episode, I have a conversation with an organization that provides an AI platform to help you overcome those. Grant Hey, everybody, welcome to another episode of ClickAI Radio. This is Grant Larsen. And today I have someone that I bumped into the not too long ago, I was at a conference and literally went to their booth and said, Oh, I want to learn more about this technology. I've been tracking your team, your organization, so it's my chance to learn more about it. And so I got to meet a Atalia Horenshtien I hope I said that right. I'm so excited to have Atalia here with me today. So first of all, "A" welcome I tell you and "B" did I say your name right? And then "C" the first question out of the box, explain the meaning behind your name. Atalia Thank you so much for having me. And you actually pronounced the name correctly. So kudos to your best. The meaning behind my name. So first of all, thanks to my parents for choosing such a unique name. It's actually a Hebrew name. I'm originally from, from Israel. And I totally I need Hebrew pronouncing it as a Talia is actually the first claim in Judaism kingdom. So it's a name from the Bible. And it's actually very unique even in Israel. Very cool. Grant Really. The queen in the Bible, I'm gonna have to go look that up. That's awesome. You should. That's very cool. Do we? Do we bow in your presence? Then? Do we do anything like that? Do we do we say Hey, this is me? Atalia No, no, no, no, not not at all. Grant Excellent. Well, thank you. Thank you for taking the time here today. Now as I understand that, I want to make sure I get this right. Your title in your organization is Global Technology Product Advocacy Lead, I actually had to write that down because I can only remember three things. And that's five words in a title, Global Technology Product Advocacy Lead for . Did I get that? Right? Atalia Yeah, that's actually correct. Grant What do you do in that role? Atalia So we did a robot. I started as a customer facing data scientist, where I work with customers in different industries, and helping them how to solve complex AI and machine learning problems. And learning from this role, and those use cases. I shifted a bit towards to the advocacy side. So how we tell the technical story of DataRobot, how we educate the market about what's possible. Some of the use cases I implement, and some of the stuff I saw was working on collaboration with our marketing sales. And our customers as well. Grant Okay, got it. So that global part, I think, is critical, because I'm assuming that you go across multiple markets, you're not focused on any one. I gotta believe that gives you a sort of broader industry cross industry view on on AI and machine learning. Is that correct? Atalia Yeah, so I was very lucky to work with different industries in different geographical locations. And obviously, I see a lot of different trends and maturity around AI, where they are in the stage, how are they adopting? What's the process? There, technical knowledge, their technical stage? Yeah. So from United States to Europe to the Middle East. It's really, really interesting. And I'm very happy that I have the opportunity to do so. Grant So that's awesome. What know what got you into this world? What got you into AI and machine learning? Atalia Actually, it's a really interesting path because I started actually the software engineer Not not a, as a data scientist, and over time, obviously the software engineer you work with, with software development, system design, etc, some stuff that you see today in in machine learning operations. And then when I did my masters, I was mostly specific around business intelligence and machine learning. And I learned a lot, it was super interesting. So I took my software skills into a different level. And it's a funny story, because a professor of mine is actually working for DataRobot. And he's one of the main reasons I'm here. Grant Oh, really? Oh, that's interesting. So was the professor already at when you were like, Okay, got it. Got it? Atalia Yep, he's still here. His name is Ted Kotler is a world class Person, both on the personality side, and he's a technical knowledge. So I'm very fortunate to work with great people in the company. Grant That's fascinating. I have a similar journey myself, meaning I too, came through the software engineering path, and then sort of stumbled into through a whole range of things into the whole data science and ML/AI space. So a lot of people certainly do that. But it's sort of a shift in the thinking, isn't it the first time you come into the ML thinking, you're thinking about your data in a much different way. And algorithms and such you're like, wait, okay, I'm solving it. So much different. But I thoroughly enjoy that. All right. So I want to get to some of the things that are unique to, to DataRobot itself. I've worked with multiple AI and ML platforms. And as I mentioned in the intro, I had been watching and looking at , watching your organization over time, take on more and more capabilities. When I when you demonstrated the latest capabilities and gave me a sense of where things are going. It started me thinking, what are the main challenges when you think about the AI and ML world? And the problems that are in this space? What are the main challenges that we face? And ultimately, I want to get to what is it that differentiates the way DataRobot does it in the market? But could you first start with what are some of the main challenges you see today, especially with your global perspective, in the AI space? Atalia Yeah. So I think the main main challenge today around the machine learning lifecycle is how you move models into productions and how you make sure your models are still accountable, and accurate with all the factors and new reality that is coming up, right. And get this today, everyone can just build psyche learn model or simple, you know, regression model. But when you work as an organization, and you have different infrastructures, different tools, different skill sets, different personas within your team, and you localize the development side of it, and every model has completely different requirements. So you're getting to inefficient lifecycle. So moving a model from development phase to production is a process that takes usually a lot of time, and it can be super complex. So something that I personally like about there rather than this is something I learned from customers, right that this is the biggest pain today is having an ability to have a platform that will be interoperable and flexible around how to support models that were created in variety of environments and languages, but also how to serve and manage and monitor models that were deployed to different endpoints necessarily to data on production server. Grant So sorry, just interrupt there. That was one of the things when you showed me I was fascinated with which was this ability to bring in models produced from a wide range of platforms and tool sets, if you will, and still bring them into the management aspect that I thought that was a critical characteristic around itself. So when when you do that work, when you bring those models in and you manage those, what is it that that you're doing that makes that easier? A it's a it's helpful for me to have one place to bring those together but be what value then does that help me with as I tried to, to update those and refactor those moving forward? Atalia So it includes several other aspects. So first of all, as you mentioned, you have a single place where you can see all your models regardless where they've been created and regardless of the word have been deployed to. So like single pane of glass where you can see everything and, and being able to see at a glance which models are stale, which eventually preventing any risk to your business. Because it's not just about having the visibility to those models. It's also the ability to manage, monitor and govern them. So what is the service health status of this model from the the all endpoints, and what's the accuracy of the model, how it's changed over time, maybe some features that have been drifted. When you see those aspects, it's really helpful for you to understand, maybe you need to retrain your existence project, maybe you need to swipe your existence model with any challenger model, something that is performing better now with the new data that is coming up. Think about COVID That can be a really great example, right? When you train models on certain data set, but then all the reality has changed. All the products you did at that time are irrelevant today with the existence data. Grant Okay, yeah. And this this ability to see the either the drip, like you said, or the staleness of that that's such a critical capability. Is that is that a visual thing? Is it notification based? And how is it that you're being made aware of this? Atalia So it's definitely a visual thing. So you have an ability to see on a specific time when something happened, but you know, we're not expecting from people to go in consistently checking the platform, you can automate the whole process with notifications, if you want to get notified that, let's say, above a specific threshold, you have, under a specific threshold, sorry, you have a drift in accuracy, you would like to get a notification. And you can automate the whole process around retraining, what are the factors for retraining? So really looking to? Where are the areas we can automate the cycle in order to make the life of the user easier? But also, you know, with how much we are saying, Yes, we have AI and we have a donation, you you still need the man or the woman in the middle to approve this process? To be aware about this process, and there is still user intervention for some degree. Grant Okay. All right. So so let's take a scenario. You know, one of the current challenges around AI is this, you know, data bias problem. So what I want to figure out is, let's say in my organization, I've got this bias that comes in, I'm not aware of it at the time, I'm creating the model. There's no intentional harm here. But however, as we get into the production and rollout in its execution, it becomes obvious that the kinds of decisions or insights are certainly leaning a particular direction, what is it that helps me to discover or find that out? And therefore ultimately, correct that? Atalia That's a good question. I think ethical AI is one of the rising topics in AI, right. And mathematically, you can create a model that is not biased. But there are some techniques on how to make sure that the model is more fair, towards your sensitive features. And actually, there are some capabilities in the platform that really helping you not just in production, actually, but also in development, where you can manage bias litigation and tag those have the features and see in your development process already. What's the what's the bias and fairness around this specific project with those features that you chose, and then being able to seeing how the bias and fairness continues towards the production side where you have new data coming in, so you have an ability to target even before and this is helpful for you to understand how to deploy the model into production? And what are the changes that are required in order to keep this model fair. Grant So it's interesting that there's some capabilities in the platform that help you to identify potential bias factors or features along the way, be mindful of that. Let's go to the far right side of this, which is let's say we've done that work. We have the model produced, it's deployed, it's in production. How do I how do I Give feedback. Is there a way to say, A? What are my results of this model? And be? What are my end users potentially feedback on it as well? It's two different kinds of feedback. A is the model given me good insights or guidance? And then be? What about the end users themselves? And how do I get their feedback into there? Atalia Are you asking in general about the model, or specifically with the ethical side of it, Grant Either one, I'm fine with either side of it. Yeah. Atalia I'm still on the ethical side of it. So we provide those visualization tools as part of our ML ops capabilities, to track the bias and fairness on those sensitive features. So you can be certain that decisions that are made with the model are aligned with your technique that you applied during development process. That's, that's one thing. And obviously, if you see any changes over time, you can retrain your model, you can try out different things as part of your development, with our bison furnace techniques. And then overall, the insights you can get from a model, they are divided to two phases. On the development side. You know, in machine learning, we're always talking about the predictions, the predictions, but this is not really the main thing. Yes, we care about the predictions, right. But how we translate those predictions into business actions. Exactly. So having an ability to get that Explainable AI, this is something that I see all the time, especially with the business personas, decision making people, for them, it's really difficult to translate, what is it? Ai model, right? So we provide some graphs to, to present insights and explainability on a model, for example, what are the main factors on a macro level, that contributing to the model? So for example, let's take a churn use case. And you're looking to understand why customers are churning. And it's not just about oh, this customer, the likelihood that this customer will churn is 0.7. What does that mean? So we know what what's the factors, for example, how many times the customer may be called to call center a lot, and maybe the customers plan is, is very expensive. So some of the factors that really affect about if the customer is churning. So from a business perspective, we can decide, oh, maybe we should improve our customer service, maybe we should reduce our pricing. So on a macro level to see those main factors, but also being able to dive into the to the micro level, and check how a change of each one of the features is really impacting the target variable. So let's say if a customer called two times twice or three times to customer service, how that affects the likelihood to churn. So this is gonna be super helpful. And this is really where we add the expandability side to, to the predictions from from the model and the predictions themselves, you know, at the end, when you move the model to production, and now you have new data coming in, you look to score it, this is where you can integrate the predictions with your business applications. For example, you know, Tableau Power BI, all those business applications. So you can still continue to work with your existing business flows and tools as you like, and being able to generate decisions. Grant But I like as he explained, or that you shared explainability is one of those elements that helps with successful adoption and usage of an AI model, and ML model. If we step back and given your experience with customer success, how would you net that if you were to look at the patterns, both the good patterns as well as the anti patterns around customer success? What have you noticed over time, across lots of markets or industries, those success patterns for not only building the models but but actually getting the value in the outcomes from AI models? What have you seen? Atalia So I think this is the million dollar question because I always say that it's not enough just to purchase an AI machine learning tool, right? It's a it's about if you if you use it, and if really models made it to production. This is how we did Robert, manage our success and with ourselves as partners, to our customers, we have an organization that is professional services, that includes data scientists that helping customers on implementing the whole process, we have some AI success. division where you have consultant, past consultant that currently working for DataRobot can do irrigation sessions with with customers and really looking to unlock the potential that they can get, and really helping them to the whole process with our professional services. So, the process can be quite long and complex. And I think it really depends also in the maturity level of the customer, because based on their skill set based on if they already have some models in productions, or if we just started a process, those things can affect about the process, because when you need to take into consideration existing infrastructures and models versus building everything from scratch, and maybe educate the people on what they can get from AI and machine learning model. So, this is a bit different between maturity, and I think everything eventually stopped with change management, you see, a lot of times you know, there is this very motivated executive buyer that is looking to change and, and include AI in the organization. But then how do you really convince the people that working on a day to day basis that this is the tool that can really help them and sometimes we see it even with data scientists that they they still like keeping, like to keep the hands on and and code by themselves without really trust any any other tools. So this is where you provide some education with some horses on the platform, but also how you engage a model that is not like a black box, right? You have expandability, you have the process, you have documentation to really let the the employees to trust the process at the output of the product. Grant So building that that trust in that, in that process sounds like the key thing there is success stories. Is there a success story that you can share where you help the organization go through this and realize some outcomes? Atalia I can try to think about some of the success stories that are publicly covered. Yes, as you know, right. For example, we have a story from Stuart healthcare. They are the largest for profit private hospital. They're operating in the US. And they use machine learning to make big decisions about staff and patients, which eventually helping them to reduce costs and improve the patient outcomes and experience. And they already started the process and really decrease the cost as they wanted. So 1% reduction in registered nurses hours paid per patient they netted $2 million in saving per year for eight of the 38 hospitals enough to its network. I think this is a great number and also a greater effect. I'm always very happy when I see those stories around, you know, hospitals and health care, which eventually provide better outcomes for society as well. Grant If you were medium size organization looking at looking at Hey, how can I apply AI/ML to my business? What would you say to them in terms of adopting a platform like like DataRobot? What What would you say? What are the things that they should start doing? Atalia So the process, in my opinion, divided for three major stages. One is the why. look internally and think, Okay, why we need to use AI? What are those use cases that I'm looking to solve? And what will be the expected improvement or our AI from those use cases? Once we define those use cases? The next question will be the how, okay, we defined the why now how we implement it. So understand the skills that they have in house and then define what to outsource versus what to build, buy versus build right, and then choose the right tool and start the implementation. And when you start the implementation, the the end result will be the what? Once we have the model in production, so how, what are the outcome that we are...
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CAIR 77: Using AI In Your Product Delivery To Leap Ahead !!
12/15/2022
CAIR 77: Using AI In Your Product Delivery To Leap Ahead !!
In this episode, I talk with the CEO and founder of an organization that has been applying AI to help them develop products. Will AI help you develop your products faster? Come and see. Grant Hey, everybody, welcome to another episode of ClickAI Radio. So today I have this opportunity to speak with one of those brains out there in the market that's being disruptive, right? They're making changes in the industry in terms of not only the problems are solving, but it's the way in which they're solving the problems using AI very fascinating. Anyway, everyone, please welcome Paul Ortchanian here to the show. Paul Hi, nice. Nice, nice of you, happy to be here on the show. Grant Absolutely. It's very good to have you here today. When I was first introduced to you. And I started to review your material what it is that your organization has put together as fascinated with the approach because I have a product development background and in in the software world. AI was late comer to that right meaning over generations when I saw the approach that you're taking to that I'm interested to dig more into that. But before we do that big reveal, could you maybe step back and talk about the beginning your journey? What got you on this route? And this map, both in terms of product development, and technology and AI itself? Paul Yeah, absolutely. So I started out as an engineer, headed down to San Francisco in the early 2000s. And, and I was more of a thinker than an actual engineer, or just be the type of guy who would figure things out by themselves. But if you were to ask me to really do things that the real things engineers do, you know, creativity was there, but not the solutioning. So being in San Francisco was a humbling experience, I guess, Silicon Valley, you get to see some really, really good engineers. So I had to make a shift in my career. And since I had a passion for user experience, the business aspect, product management was a great fit a function I didn't really understand. And I got to learn and respect, and did that for about 10 years. In the mid 2000s, and 10s, I basically moved back to Montreal for family reasons and cost of living, of course in San Francisco. And I started a company called Bank Biddick, which in French stands for public bath. And the idea is that most what I realized in Canada was that people here in accelerators, incubators and, and startups just didn't understand what product management was. So they didn't really understand what they do and how they do it. And I saw a lot of organizations being led by the marketing teams, or the sales team and being very service oriented and not really product LED. So basically, it basically stands for public bath, which means every quarter, you want to basically apply some hygiene to your roadmap, you have a galaxy of ideas, why not go out there and just, you know, take the good ones and remove the old ones and get rid of the dirt. And we started with that premise. And we put we said, well, what does a product manager do on a on a quarterly basis? Because a lot of the material you'll read out there really talks about, you know what product managers should do in terms of personas and understanding the customer's data and this and that, but nobody really tells you which order you should do it. Right. If that was my initial struggle as a product manager, do you try to do it all in the same day and then you realize that there's not enough time? So the question is like in a one quarter 12 week cycle, as my first three weeks should be about understanding the market shifts the industry, the product competitors and and the users and then maybe in the next three weeks working with leadership on making sure that there is no pivots in the organization or there are some some major strategic changes and then going into analyzing the DIS parking lot of ideas and figuring out which ones are short term and re and making business cases in order to present them for, for the company to make a decision on What to do next on the roadmap. So there is a process and we just call that process SOAP, which goes in line with our public bath theme. So the idea was like, let's let's give product managers SOAP to basically wash their roadmap on a quarterly basis. And, and that's what being public does. And we work with over 40 organizations today so far, on really implementing this product LEDs process within their organizations, we work with their leaders on identifying a product manager within the organization and making sure that marketing support sales, the CFO CEO really understand how to engage with them what to expect from them, and how product manager can add value to to the organization. And so they just doesn't become, you know, this grace towards them as many features as you can pump out, right. Grant Oh, boy, yeah. Which, which is constant problem. The other thing that I've noticed, and I'm wondering if, and I'm sure that your SOAP methodology addresses this, it's the problem of shifting an organization in terams of their funding model, right? They'll come from sort of these project centric or service centric funding styles, and then you've got to help them through that shift to a different funding model round products. You guys address that as well. Paul Yeah, we address that a lot. One of the things we always tell them is if you are a service professional services firm, and you know, I have no issues basically calling them that. If and I asked them like do you quantify staff utilization in percentages, like 70% of our engineers are being billed? Right? Do we basically look at the sales team? How many new deals do they have in terms of pipeline? Are we looking at on time delivery across those, so double use that to serve the sales team closed? And what is our time and technical staff attrition, that usually tends to be identifiers of you being a service firm? And we often ask them, well, let's let's make the shift, when we identify one little initiative that you have that you want to productize because they all these service firms, really all they want is recurring revenue, then the service is tough, right? That you constantly have to bring in new clients. So this recurring revenue, the path to recurring revenue is, you know, being able to say, Okay, I'm going to take two engineers, one sales person, one marketing person, one support person, and a product manager. And those guys collectively will cost me a million dollars a year, and I'm going to expect them to basically bring me $3 million in recurring revenue. That means that they're, they're no longer going to be evaluated on staff utilization, they're no longer going to be evaluating the number of deals they're bringing in. And they're, they're really going to be evaluated on how are they releasing features? Are they creating value for those features? are we increasing the number of paid customers? And are we basically, you know, staying abreast in terms of competitors and market industry changes. And so that's a complete paradigm shift. And that transition takes a while. But the first seed is really being able to say, can you create an entity within your organization where the CFO accepts that those engineers are dedicated and no longer being, you know, reviewed in terms of their utilization rate in terms of their know how much they're billing to customers? Once they do that shift in the recipe is pretty easy to do. Grant Yeah. So it's become easy. So the thing to I've seen and experienced with, with product and product development is the relationship of innovation to product development. And so I see some groups will take innovation, and they'll move that as some separate activity or function in the organization, whereas others will have that innate within the product team itself. What have you found effective? And does self addressed that? Paul Yeah, I mean, we always ask them the question of what how are you going to defend yourself against the competition with the VCs that have to call their moat, right? And that defensibility could be innovation, it could also be your global footprint, or, you know, it could be how you operationalize your supply chain make things really, really cheap, right? Every company can have a different strategy. And we really ask them from the get go. We call this playing the strategy, we'll give them like eight potential ways a company can, you know, find strategies to differentiate themselves? And the first one is first the market? And the question is, it's not about you being first to market today. But do you want to outpace your curlier closest rivals on a regular basis? And if so, you know, you need an r&d team and innovation team who is basically going to be pumping out commercializable features or r&d work. And then we always give him the two examples, the example of Dolby Dolby being completely analog in the 70s, but really banking on their r&d team to bring him to the digital age and from the digital age to set top boxes to Hollywood and now into Netflix compression, right? So they basically put their R&D team as the leader to basically keep them a step ahead of their competition. But it but on the other hand, we also Welcome, you know, talk about Tesla, where Tesla is basically doing the same thing, but they're not doing it for intellectual property like Dolby, they're not suing anybody are actually open sourcing it. But there's a reason behind it where that open sourcing allows them to basically create the, you know, what we call the Betamax VHS issue, which is making sure that there's compatibility across car manufacturers for Tesla parts and overproduction of parts that are Tesla just to increase their supply chain, right? So we ask them, Do you want to be that company, if you don't want to be that company, then there's other ways for you to basically create defensibility, it could be regulatory compliance, if your industry requires it, you can go global, you can go cross industry, you can basically create customer logins, how just how SAP and Salesforce love to basically just integrate workflows with like boots on the ground, professional services certified teams, right? And or you can basically review your process and make sure just like Amazon, that you're creating robots to do human work in order to just basically do it cheaper than anybody else. So there's ways of doing it. And I would say that if you were in AI space, especially, you know, it's important to make sure that, you know, are you really trying to innovate through AI, because you can get a lot of researchers doing a lot of things, but that's not really going to help you create commercializable ideas. So from the get go, the leadership team needs to, you know, at least make a hedge a bet on, you know, expansion, innovation, or creating efficiencies and just, you know, decide and let the product management team know in which direction they're gonna go planning on going for the next six years. Please. Grant I love your last comment there, Paul about about getting the leadership team involved. It seems that many times in organizations, this challenge of making the change sticky, right, making it last making it resonate, where people truly change their operating model, right, they're going to start operating in a different way, their roles and responsibilities change, what is the order in which things get done all of those change, when they start moving both into this AI space, but you know, product driven just by itself, even without AI has its own set of challenges? So here's the question I have for you. As you move companies through this transformation, that's part of your business, right? You are transforming the way companies operate and bring about better outcomes. How do you make those changes sticky? Because this is a cultural change? What is it you guys have found it's effective? Paul Or it goes back to our name public bath and SOAP, right? Because the idea is, you take a bath on a regular basis hygiene is something you do regularly, right? So we ask these organization, if we give you a process where you know exactly what the product management team is going to do with you with the leadership team in order to prioritize your next upcoming features, then can you do it in a cyclical way, every quarter, you need the product manager do the exact same process of revisiting the competitors, the industry, the market, as well as like the problems that you have with your premature customers, bringing it back to the organization, asking if the strategy is still about expansion, innovation, efficiencies, identifying new ideas, clearing up the parking lot of bad ideas, etc, and eventually making the business case for the new features in order for them to make a commitment. So if we do this in a cyclical way, then the product role becomes the role of what I'd like to call the CRO, which is the chief repeating officer, because all the product manager is doing is repeating that strategy and questioning the CEO, are we still on? Are we pivoting or if we pivot? What does that mean? And if you're doing it on a three month basis, what that allows your company to do is to make sure that the marketing and sales and support team are going along with what the engineering team is going to be delivering. So this is what I usually see most product organization where a decision has been made that the engineers are going to be building a particular feature, the sales and marketing team just waits for the engineers to be Code Complete. And once a code completes, done, they're like, Okay, now we're gonna promote it. But my question is that it's too late. Right? You really need so I always show the talk about Apple, how Apple would basically go out in front of millions of people and just say, here's the new iPhone 13. And we came up with a new version of Safari, and we're updating our iOS and we're doing a 40 Other changes. And the next thing you want considered an Apple store and you know, everything has changed. The marketing has changed the guys that the doing the conferences, and the lectures and the training are all talking about the new supplier, the new iPhone, and you ask yourself, How did how did Apple know and to organize the marketing support and sales team in that in such a way that the day that the announcement has been done? Everything is changed. So that means that it's not just the engineering team's responsibility to get to Code Complete. It is a collective responsibility where marketing support and sales are also preparing for the upcoming releases. And and the only way you can get that type of alignment is If every three months these these parties, technology, product, CEO, CFO, sales, marketing and support can get together and make a clear decision on what they're going to do, and be honest enough of what they're not going to do, and then work collectively together on making sure that that those are being delivered and prepared in terms of the size of the promotion that we're going to do, and how are we going to outreach how's the sales collateral going to change? How is the support team going to support these upcoming features. And so everybody has work to do in that three months timeframes. So and then that if we can get to that cyclical elements, I think most companies can create momentum. And once that momentum has is generating small increments of value to the customers, then you base start start building, what I like to call reputational capital, with the clients, with the customers with the prospects. And eventually anything you release the love, and everything you release adds value. And eventually everybody loves everything you're doing as an organization become that, you know, big unicorn that people want to be. Grant Yeah, so the net of that is, I believe what you said as you operationalize it. Now there's it gets integrated into everyone's role and responsibility. It's this enterprise level cross functional alignment that gets on a campus. And the cadence is, in your case, you'd mentioned quarterly, quarterly sounds like that's been a real real gem for you. I've seen some organizations do that in shorter timeframes and some much longer. It sounds like yeah, at least quarterly is that a good nugget that you find there? Paul Yeah, quarterly works, because you know, markets are set in a quarter way they operate in that way the you want results on a quarterly basis in terms of sales in terms of engagement, etc. But what's important is that which you know, a lot of engineering teams like to work agile or Kanban. And in a quarter in a 12 week timeframe, you could fit, I'd say, Let's see your Sprint's are three weeks, you could fit for sprint for three weeks variance, or you could fit six 2-week sprints. But I feel that if you were to shorten it, then the marketing team and sales teams supporting might not have enough time to prepare themselves for Code Complete, the engineers might be able to deliver but then the product manager gets overwhelmed because doing an industry research, competitor research etc. Every, say month and a half or two months just becomes overwhelming for them. Because things don't change enough in two months for them to be able to say, Oh, look, this competitor just came up with that. And now we need so so I think three months is enough time for the world to change for, you know, country to go to war for COVID to come over and just destroy everything. So pivot decisions are usually can pretty good to do on a on a quarterly basis. Grant Yeah, that's good. That's, I think COVID follow that rule. Right. Hey, I have a question for you around AI. So how are you leveraging AI in the midst of all this? Can you talk about that? Paul Yeah, absolutely. So what we noticed is a lot of organizations who have products, so SaaS products, or any type of product, IoT products, etc, they're generating data. I mean, it's it comes hand in hand with software development. So all that data is going into these databases are and nobody knows what to do with them. And eventually, you know, they want to start creating business intelligence, and from business intelligence, AI initiatives have just come about, it's very normal to say, You know what, with all this data, if we were to train a machine learning module, we would be able to recommend the best flight price or the best time for somebody to buy a flight, because we have enough data to do it. So so we're not working with AI first organizations who are here we have, our entire product is going to be around AI, we're just trying to work with organizations that have enough data to warrant 1-2-3, or four AI initiatives and an ongoing investment into those. So the best example I like to talk about is the Google Gmail suggestive, replies, right, which is adding value to the user needs AI in the back, end a lot of data. But ultimately, it's not that Gmail isn't AI product, it simply has AI features in it. So and when organizations start identifying AI or machine learning, predictive elements to their product, then we go from engineering being a deterministic function, which is if we were to deliver this feature, then customers will be able to do that to a probabilistic function where Let's experiment and see what the data can give us. And if this algorithm ends up really nailing it, we will achieve this result. But if it doesn't, then do we release it? Do we not release it? What's the and then it gets a little bit hairy because product managers just lose themselves into it. Oftentimes, they'll release a feature and the sales team would just ask them to pull it out right away because it has not met the expectations of a customer or two. And ultimately, like what we ask product managers to do is work with leadership on really it Identifying a few key elements that are...
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CAIR 76: How to Be an Entrepreneur AND Hold a Full-Time Job!
12/03/2022
CAIR 76: How to Be an Entrepreneur AND Hold a Full-Time Job!
In this episode I talk with Dr. Pranay Parikh, where we look at the question, how can you do your full time job while being an entrepreneur to fill the gaps that are missing in your life? Grant Hey, everybody, welcome to another episode of Financial Investing Radio. So today I have this opportunity. It's taken us a few times for me to chase him down. He's very busy. Dr. Pranay Parikh. I'm excited to talk with him when I when I first saw the profile on him and realize the journey that he both has done and the one that he's on and his vision of that I got to talk to this gentleman. I'm gonna read his the little clip that I got before even let him say a word. I just want you to hear a little bit about him. Alright, here we go. Okay, hold on. Here we go. It's Dr. Pranay. Parikh is a physician co founder and president of ascent equity group, a serial entrepreneur, we're going to want to ask him about that. Okay, online course creator and host of the MD to entrepreneur podcast, which is really cool. Continuing on his unconventional journey, and I add it is which is what makes us really cool. His unconventional journey to medicine helped him learn the skills to excel in entrepreneurship. He's launched a seven figure online course. And he's bought over $1.1 billion in real estate. Wow. And he's helped hundreds of physicians launch their own businesses. His goal is to help launch 10,000 physician led businesses. That's amazing. So I want to welcome here to the show. Dr. Pranay Parikh. Welcome. Pranay Thanks, Grant. I'm super excited to talk. Grant It's so good to have you here. Now, we were both talking before we got started. We're both in the southwest part of the country. We sort of enjoy that. In fact, I think you and I might have even had our earlier grown up years in the Northern California area. So we got a lot in similar but the key difference is, I am definitely not a doctor. You know, I went bought band aids last night. And it took me awhile just to figure that out. So I'm more of a tech and investing guy. But I am not a doctor guy. But I'm excited to talk to you about this and your journey. So thanks again for being here. Pranay Yeah, super excited to talk to you and your audience. Grant Okay, now something happened, right? You were growing up and you said, hey, I want to be a doctor and you got moving down that path. But somewhere along that line, well, first of all, what kind of medicine? Have you been practicing? Pranay So I did a residency in Internal Medicine, and I practice hospitalist medicines. So that means if you ever have to spend a night in the hospital, then I'd be your doctor. Grant Okay. Is that is that the same as as an internist? Is that? Is that what that is? Pranay Yeah, so it's the same residency, but usually what internists do they do outpatient medicine, so you know, your primary care doctor, they do some inpatient, but I'm kind of sub specialized. I only see people in the hospital, the hospital itself. Grant Okay, got it. Very good. All right. So you were on that journey doing that work. And something happened somewhere along the line, you sort of sat up and said, I need to add something, either to my life or my purpose or my vision on top of this medical route. Tell me about that. What happened? Pranay You know, so it's kind of funny. So to get into medical school, you have to be well rounded, right? You have to be doing all this other cool stuff, right? You can't just be a nerdy like I was really good at Sciences and maths and all that stuff. They want someone you know, reads a lot of the books and does all this stuff. But after you get in all that stuff gets taken away gets subtracted. And it kind of sucks for people like me that like doing a lot of other stuff, but you're so busy in medicine, doing your job learning that there's not much else you can do. So as soon as I got an opportunity to start doing other stuff I did. So for example, in medical school, I used to hold art shows. And then the money that we grades go to the doctors without borders, I was always trying to do stuff that was, you know, a little bit outside the box. So as soon as I graduated finished everything, I was like, okay, what can I do? What? Where can I go and all this stuff that's been suppressed for so long. Grant That's amazing. You talked about Doctors Without Borders, I have a friend just Sunday night I was talking with he, he spent a number of years I think went five times down to Central America, they were taking both dental as well as medical help and support into some of those areas there. It's fun to hear the service and the blessing that that is to people that are missing those things. So you did these art shows that was providing support to them. That's a cool thing. So it sounds like there was either there's altruistic thing that you needed to get filled in your life, right? I mean, something to reach out further, in addition to the work you're doing that led you to doing this kind of work. Now, there's that what led you at some point to say, I'm going to build sort of a business or be an entrepreneur on it is that what led you down that path? Pranay Still, so you know, when I when I looked at the landscape after being graduated, you know, at a pretty decent salary, but I realized the most important thing is what I do with that money, not how much I can make, you know, I could have just gone and bought a car or bought a house. And I'd be, you know, I wouldn't have a ton of money to consider for my future, right. So I decided to rent a little bit longer, keep driving my Honda Accord, which actually still have 2012. So you know, it's what I do with the money. So you know, I did the stock market, but in this world, people that are most well off and buy well off, you know, I don't care about the total number that's in my bank account, I care about freedom, I care about providing for my family, and I care about providing for my extended family. So the people that I've seen that been have been able to do that are the people in business, business and real estate. So I thought how, how can I incorporate one or, you know, fortunately, now, both of those into my life? And what's the quickest way to do that? Grant Okay, excellent. So you have a broader vision about, I want to make a difference, right? I want to help someone in the world, what not just my own family, but but the people within my reach that I can access or get out to? Is that right? Pranay Yeah. And as a doctor, it was great. Because I there's a lot of job satisfaction and being able to help people. But I was limited by time. And that's, that's one of the big issues that I had, I wanted to create this impact. I wanted to help as many people as possible, but there was only one of me, right? So if I'm not at the hospital, I'm not helping people. So how do I take that impact that I want and spread it to, really the whole world, and the what I thought was, if I can help other people, after I got my business up and running, I can help other people get their business up and running. And if they're able to either find financial security and be happier doctors, you know, you might have heard of this epidemic of a burnout, that's just been an issue. And a lot of that is not being able to pick your own hours and being forced to do things that you don't necessarily want to do a lot of administrative work. And if you're able to take control of your life, then those happy doctors are making a bigger impact. And that's something that I can, I can help people do as well. Grant So you're going after this audience of people that have proven that they have the ability to be disciplined to dedicate their time and their resources, their energy, not just to not just to their practice in their craft, right around medicine, but but now to take that and apply it to businesses. And those businesses the purpose of those sounds like have twofold one is to provide an outlet for them sort of emotionally, right where they can get outside and, and maybe really, you know, benefit their own family but also to use their businesses away then to further their reach to help people when they're away from practicing their medicine. Did I get that? Right? Pranay Correct. Correct. And you'd be surprised how often someone comes up to me and says, Hey, Pranay, I'm just a doctor. You think I could start a business? And it's funny because you have to get to get into medical school or, you know, dentistry lawyers, and I'm just talking about medical school because that's what I've been through. But you know, any professional degree, you've gone through a lot. You've studied, you've been taking all these tests and you've really stood the test of time. So you can pick up a lot of these other things pretty easily, you know, a little bit of trial and error. So a lot of it is just showing people that they have this innate ability. And a lot of times in medicine, we're taught not to try something, unless we have 100% chance of success. Grant It's interesting is about a year ago, I was running a class for a group of people on starting your own business. And, and one of the people that came into that class was an oral surgeon, and doing doing just great, you know, in terms of financial, right. And I said to him, why, why did you take this right to mean, you certainly don't. Okay. I mean, and he said, well, the, the one area that he felt like he was running into that it was creating a challenge for him was that, while he had figured out and was successful at the procedures, at some point in the career, those procedures became procedural. In other words, I was just doing I'm quoting him, I was just doing and still doing the same thing every day. And what I found that I couldn't do is I couldn't be creative, right? I mean, that wouldn't be the right thing, either for the safety of the patient, right, or for other reasons. It's not like I can say, well, I'm going to try this procedure. And other way. There's other times and places maybe to do that, but not while you're, you know, doing the the surgery. So he said there was a gap in his life was, he needed a way to be able to express himself and be more creative, and let that part of his personality have a place to do things. So he was starting a business on his own. And I'm wondering if, if that resonates with you, if that's also part of what was in your mind as well. Pranay Yeah, and you know, after and there's usually a slump, three to five years after you're done with school, you feel confident in your abilities. And a lot of times that challenge is gone, you know, it comes here and there. But that that daily challenge that you're, you're racing against the edge is gone. And it's nice to go into something that you have no idea about, you know, starting a business, starting your own practice starting a podcast like yours, and it's invigorating, trying to figure things out, you know, and, and failing and being successful and getting that first download and 10th Download, and so on. Grant There is something to that, isn't it? It's this, what's my next hurdle? Right? What's the next thing? You know, can I do this right? Can I grow or expand in that area? And so I think sometimes in that profession, well, not just that profession, others as well. But being able to have that side hustle, or that side practice helps to fill that out. And to round you out. That doesn't mean you step away from it. Now, maybe some do. In fact, on that topic, do you still practice then today in medicine? Or are you full time over in the sort of business and investing side? Pranay I actually still practice and most people are very surprised, given all the other stuff I do. I'm at around point eight full time, I probably need to cut down a little bit more. So at the end of the year, I'll probably do point five, but it's nice to keep my foot in the door a little bit. You know, like I said, I enjoy it. And it is using a different side of my brain. Grant Yeah, yeah, absolutely. Okay, so let's talk about, let's talk about that entrepreneur side of you then. So you went to real estate, because you said you saw that those that had achieved some level of freedom. Were doing business and real estate, and you sort of found that pattern there. Right. You talk a little bit about what it is that you do with that business. Pranay Yeah, you know, and so a little bit about the beginning, in medicine a lot of the times is you're learning from colleagues, you know, it's like Socrates, instead of more of a professor to student, there's some of that as well. But after your practice, seeing I reached out to my colleagues all the time, I asked them what they think so, you know, when I first learned about real estate as I thought, there's not that much people teaching how to invest in real estate without being a landlord. And I looked around, I looked around, there wasn't anything. So I went with my partner and said, Hey, let's create a course that will teach people how to do this, right? And we thought we were done after that. And after a couple years of doing that, we've had 1000s of students, people say, hey, you know, we learned we'd like what you say, but we don't actually do want to do the work. We want you guys to find the deals to negotiate, and most importantly, to follow up to make sure that the person who's running the day to day is doing what they say they're doing. So we created really almost like a bespoke, passive, real State, a private equity company called the cent equity group where we go out we find best in class operators that have done this for 2030 years. And when we partner with them, we negotiate for the best terms. And most importantly, there's many people that do that. But most importantly, we have a full asset management, we have a full team that if something goes wrong, we could take over the property. However, that team, they're really focused on the big picture, how do we maximize profit? And, you know, not really doing the day to day like talking to maintenance, finding about leases? How do we maximize profit for our investors, and, you know, we have at this point, hundreds, almost 1000 investors, mostly doctors, but some dentists pharmacist, and we really want to create the best real estate investment, that it takes the least amount of work. So I own a couple rental properties myself, I have a property management, property manager, and it's still work. You know, I don't want to really work very hard for my investments. But that's just me. Grant Yeah, that makes sense. So wait, can you talk more Pranay about where the investing is? Is it raw land, single homes, this apartments are commercial? You talked about that? Pranay Yeah, so we, you know, we do bread and butter. And we kind of focus on people's needs, right? And people need a place to live. And what happens when, like right now we're heading towards a recession or mortgage rates are going up. People go into apartments, I've lived in apartments in the past. So what we do middle the ground, what is often called Class B, like boy, apartments, where when times are good people will move up into when times are bad people will downgrade from, you know, the nice downtown apartments to you know, maybe a little bit further away. And, or maybe they can't afford a house or they don't want to buy a house. And they go to class B. So that's the type of stuff that we've like, because it's recession, recession resistant. And even in 2008, the default risk was less than 1%. Because apartments are safe and stable. Grant Yeah, safe and stable. Another key part of that seems like the demographics and the geography. In other words, where these are located. Do you target a specific part of the country? Or where do you focus? Pranay Yeah, yeah. So we call it the business friendly states. It's kind of along the Sunbelt. And this has been a trend. We've seen it a lot more in the past, since 2020, after COVID, but it's been ongoing for five to 10 years, people are moving to areas that are more affordable outside of coastal cities. And now with all the remote work, there's there's no reason really to live in the coastal towns, you might as well live where you can afford, and they're starting to get, you know, robust neighborhoods and cultures and all that great stuff. Grant Nice. And when you when you think about the kind of profile, right, can you describe what does that look like in terms of the perfect person that you would bring into the ascent group? Meaning that you're focusing on the doctors, right, but is it someone that's done with medical school? Or is it Are they on their way? Or they they're 10 years down into their career already? I mean, what does that look like? Pranay Yeah, so all our deals have to be accredited investors, meaning that you have to make more than 200,000 per year, for two years, or 300 as a couple for two years, or have a net worth over a million dollars. And that's, that's not our requirements. That's the Securities and Exchange Commission by the government. So as long as they qualify for that, we're happy to take anyone, mostly doctors, but we have a ton of dentists. And it's usually, you know, they have to have two years of tax returns. So people started investing two years after they graduate, and then all the way towards the, you know, latter part of their career. So it's, it's nice, it creates stable income. It's tax deferred. So it's money you can start using, and there's a lot of tax benefits. So doctors especially like the type of investment. Grant Yeah, is it? Is there a certain commitment time? So in other words, are you expecting people will get involved for a five year period or 10? Or what does that look like? Pranay Yeah, so our deals, we tend to go on the lower end. So three to five years, that means you put in your money, you get your money back? Usually 1.8 to double your money in about three to five years just depends on the deal. And minimum is usually around 50,000. And we have that at that amount because it's really easy for people to get me on the phone and any of the principals who are all doctors And we want to create really a high quality great communication system. Because, you know, even if you're able to put down 50 102 50 It's scary. I don't care how wealthy you are, it's scary putting your money down. So we really pride ourselves in having great communication. Grant What impact have you noticed on this investing strategy with, you know, the increase in inflation rates that's been going on as well as mortgage rates is had some impact on this? Pranay Yeah, so and this is really important for people who are looking at these types of deals, also called syndications. People might know it as that the two things I'd really look at right now, to bet a deal is to sponsor you know, people who are running the day to day, that kind of makes sense. But the second is the debt. So interest rates are crazy right now. So I would try to get a fixed rate debt, you know, meaning that it's, you know, three to five years. So for example, our last deal that's close now, we had nine years at 2.9%, Raizy. And then four years of interest only. So we really go out and try to find deals that we think have a ton of downside protection. So the one of the most important things, it's always been important, but even more so is what type of debt or mortgage the people are getting. Because if anything's gonna go wrong, it's, you're not going to be able to cover your mortgage payment, and the bank takes the property back. Grant That's amazing, you share that, you know, I look at the interest rates today. And they are obviously higher than than they were just, you know, last couple of years. But it reminds me of when my wife and I had just gotten out of college, and this was late 80s. And we were in Chicago, and we were buying our first property. And interest rates were really high. I mean,...
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CAIR 75: Real Estate Returns Too Good To Be True? The Land Geek...
08/06/2022
CAIR 75: Real Estate Returns Too Good To Be True? The Land Geek...
Today I had the opportunity to speak with "The Land Geek". Fascinating conversation. He's got over, well over four and a half million downloads on his podcast. He's got some interesting ideas and insights on investing with land that the returns higher than normal, I guess normal, what's normal, higher than, you know, eight 10% return, if you will, returns on these investments. So I'm very excited to have Mark here with me today. Thanks for joining us, we learn the secrets from the land geek. Everybody welcome to another episode of Financial Investing Radio. So I have been chasing this person for some time. He is super busy and has an amazing profile. I hope you take the opportunity to look into what he's done. We're going to be having conversation today with Mark, Oh man, Mark. I didn't even ask at a time. Podolski! Mark Perfect pronunciation. Grant Did I say that? Okay. All right. Very good. Mark. Welcome. Thank you for being here today. I appreciate it. Mark Grant Larsen, an honor. Privilege. Thank you. Grant You know, we found out that we are not too far from each other geographically, which is a real treat. There's some neat, neat things about the part of the country we live in for sure. Mark Absolutely. We've lost our complaining privileges living in Scottsdale, Arizona. Grant That's right. That's right. That's right. Even when it gets a little hot. I've learned to quit Quit complaining about it's not a Houston hot right. Mark Houston hot. It's 80 degrees in the pool. Grant Yeah, that's. That's right. It's fixable with the pool. That's right, right. Okay, so the land geek, you are known as the land geek, you've done a great job getting your name out there as land geek, not only getting your name out there, but proving a framework. But we'll get to the framework here in a moment. Because what you've done is pretty unique compared to other real estate investing strategies that are out there, of which I actually participate in some of those others, right, but I won't get to that yet. So I'm interested to learn more about what you do here. But let's back up. You were doing what what got you started to say I'm gonna go after land investments in this way. Mark So if we rewind the tape now, to 2000 I was a miserable micromanaged. 45 minute commute to work and back investment banker specializing in mergers and acquisitions with private equity groups. And grant it got so bad for me. I wouldn't get the Sunday blues, anticipating Monday coming around. I'd get the Friday blues, anticipating the weekend going by really fast. And having to be back at work. On Monday. I was pretty much yeah, really blue. So I first hired this guy, and he's telling me that as a side hustle, he's going to tax deed auctions. He's buying raw land, pennies on the dollar. He's flipping them online, and he's making a 300% return on his money. Grant. I'm looking at companies all day long. And a great company great has 15% EBIT on margins are free cash flow, average company's 10%. And I'm looking at companies all day long, less than 10%. So of course, I don't believe them. And I've got three grand saved up for car repairs. I go to New Mexico with them. I do exactly what he tells me to do. I buy 10 Half Acre parcels and average price of $300 each. I flipped them online. And they all sell for an average price of $1,200 each. It worked. So I went to another auction and in Arizona, where we live. And again, this is 2000 There's no one in the room. I'm buying up lots of acreage or nothing. And I sell all that property. You know that what auction I made over $90,000 So I go to my wife. She's pregnant at the time. I said Honey, I'm going to quit My job and become a full time lead investor. And she said, Absolutely not. Yeah. Grant What do you say? And what are you doing on? Mark Yeah. So it took 18 months for the land investing income to exceed the investment banking income. And then I quit. I've been doing it full time ever since. And I absolutely love it. Grant That's incredible. So you just sort of stumbled into it, someone happened to say, they'd already sort of figured this out. Now, it sounds like what you did with that is after you've done this for a while, you've created a system out of this, then is that right? Mark Yeah, I mean, after a while, you start picking up things, and you start seeing, okay, well, how do I make this job, myself. And, really, my whole philosophy is, I can always make more money, I can't get more time. And so we want to use three levers to scale and grow a business, other people's time, software and automation, and other people's money. And so once I combined all three of those, I was really able to grow and work really about 30 minutes a week, in my business. Grant What, 30 minutes, you're at a point now where you work 30 minutes a week on your business? In the business? Yeah, that's amazing. Wow. But it took that scaling, right, took that automation to figure it out the team around you to help take care of certain aspects of it took all of those pieces, as well as other people's money. That's interesting. That took five years. Oh, that was gonna ask you so five years to get to that point, learn the lessons, learn the business processes that you should automate, and so forth. Right? Mark Well, five years just to start getting myself out of business, probably another five years, to get to my point where I can work 30 minutes, 30 minutes in the business, rarely, I'm just meeting with my Acquisition Manager. And we're looking at the numbers and saying how many deals are pending? How many offers went out? How many deals will be closed? How can I support you? Grant So when it comes to finding these opportunities is the auctions is that your main input, or source or how well find these. Mark So Grant, I'm going to walk you exactly through how I do it. So you live, I'm gonna use these as a case study. You're in Scottsdale, Arizona, but let's assume that you own five acres of raw land in Texas, and you owe $200 in back taxes. So essentially, you're advertising two important things. Number one, you have no emotional attachment to the raw land, you're in Arizona, the properties and taxes in Texas. And number two, you're distressed financially in some weird way. Because we don't pay for things like our property taxes, we don't value them in the same way. As resolved, county treasurer, keeps sending me notices saying, Grant, if you don't pay your property taxes, you're going to lose that five acre parcel, tax deed or tax lien investor. So all I'm gonna do is look at the comparable sales on your five acre parcel for the last 12 to 18 months, I'm gonna take the lowest comparable sale, let's say $10,000 and divide by four. And that's gonna give you a Warren Buffett would call a 300% margin of safety. So I'm gonna send you an actual offer on your five acre parcel for $2,500. Now you accept it. Why? Because for you $2,500 is better than nothing. In reality, three to 5% of people accept my quote unquote, top dollar offer. But now that you've accepted it, I have to go through due diligence or in depth research. I have to confirm you still own the property. I have to confirm back taxes are only $200 I have to make sure there's been no breaks in the chain of title. There's no liens or encumbrances. And because it's only $2,500 investment, I outsourced to my team in the Philippines, connected to an American Title Company. It cost about $11. I was investing $5,000 or more, I wouldn't take any title risk. You have to close traditionally through a title company. But since this is a smaller deal, everything checks out. And now I'm going to sell your five acre parcel 30 days or less and make a cash flow. So I have a built in best buyer grant. Do you know who it is? Who is the neighbors, the neighbors? So I'm going to send out neighbor letters saying hey, here's your opportunity. Protect your privacy. Protect your views. Know your neighbor. So oftentimes the neighbors will buy now if the neighbors pass a gun to my buyers list, if they pass. A good little website you may have heard of, it's called Craigslist is the 15th most trafficked website United States. I'll go to one I know you've heard of called meta, or Facebook, buy sell groups in the marketplace, and then I'll go to the lands land moto.com lands of america.com land and farm.com land flip.com Land hub.com These are platforms where people buy and sell raw land. But the way that I'm going to do it is the secret. I'm going to make it irresistible for my next buyer. All I'm going to ask for is a $2,500 downpayment, to control this five acre parcel, and then I'll make it a car payment, let's say 297 a month, for the next 84 months at 9% interest. So it's a one time sale, I'll get my money out on the down payment. I could go six to 10 months out. And now I'm getting a passive income of 297 a month, next 84 months. No renters. No rehabs, no renovations, no rodents. And because I'm not dealing with a tenant, I'm exempt from Dodd Frank RESPA. And the SAFE Act, all this owners real estate legislation. So grant, it's a simple game, can I create enough land notes where my passive income exceeds my fixed expenses? And now working? Grant Because I want to not because I have to guess you have to? So on those numbers, then Mark, when you look at that, and what's the percentage of those that carry all the way through, you know, you're obviously I love, I love how you have the profile for that best buyer, how you create that, that passive income, what sort of risks does that put on your shoulders, where there's potential for them not following through on the cash flow, any issues there? Mark We don't mind it, because we use a land contract. And a land contract means that we can we still own the underlying asset, while they make payments. If they default, they have 30 days to cure their default. If they don't, we keep the down payment, we keep the monthly payments, our cost basis goes lower, we resell that property, we get a new down payment, we get new monthly payments, and extends out a return on investment is... Grant Oh, that's awesome. Mark So I've been investing my wife and I invest in real estate, but it's it's on. It's with the tenant model, right? It's, you know, creating sort of the cash flow on that site. And it has some of the challenges and headaches you're talking about. Right? It's I deal with property management organizations, I deal with tenants that aren't following through blah, blah, blah, blah, all that. And so this is appealing to me to be able to say, hey, you know, I don't have to worry about about that. Grant Is there a return that you felt like is higher taking this strategy than taking that sort of tenant based model? Mark Well, our average return on cash is 300%. And on terms, it's 1,000%. Grant That's crazy. Because we you know, typically fight for eight to 10 or 15%, right? In this in this renter model. So that's, that's fascinating, fascinating approach. So a couple things here. The average hold time. So you'd mentioned 30 days, are you literally flipping these in a 30 day timeframe? Is that the average? Mark Yeah, that's average. Now, if it's more than 30 days, something has to change. Maybe we have to raise the downpayment, maybe people think it's too good to be true. Maybe we have to lower the downpayment, maybe we have to raise the price, lower the price, change the interest rate, change the terms, something needs to change, maybe it's as simple as the headline is conducting. So that's our litmus test for what's wrong with our app. Why did that? Why is this not selling 30 days? Grant What's the what's the benefit of turning it into that passive cash flow as opposed to just flipping and taking the cash right now all of it out of the deal and walking away with that in your pocket? Mark Well, cash is a problem, right? Because now I've got to do it all over again. And I've just created a really hard job for myself. So I'd rather buy the asset one time and hold it for as long as I can and have a cash flow rather than flip a tax. Hopefully, I get another deal flip, pay tax, the market could turn on me. Right? I've been I've overpaid and I'm stuck with an asset. Grant Yep, makes makes total sense. So I noticed on your on your on your . I noticed on there you you've been creating quite a nice playlist for a long time describing some of the challenges the hurdles the things people might deal with some tips and techniques around that. You've been publishing for quite a while on this. If someone were to get started on your YouTube channel itself, you've got this nice entry YouTube video right there passive income without headaches explained. I love that as your entry one. I watched that and you walk through much of the framework that you just described here today, what would be some of the hurdles that you think people will run into? Or that you've seen people run into where, where this doesn't work? Mark Well, you know, the biggest hurdle I think, for people who get started is they think, can I do this in my backyard? Well, if you live in San Francisco, no, no one's gonna sell you an infill lot. 25 cents on the dollar, they're gonna go the biggest, baddest land broker in town. If you live in Manhattan, same thing. So we're looking at properties an hour to three hours from the nearest town. And also, there's 3007 us counties like where do you start? So if I live in Iowa, let's face it, nobody wakes up next boy, I'd like to buy some land today in Iowa, unless you live in Iowa. So to get your biggest buyer pool, you want to be the southwest, little bit the Northwest, California and Florida. These are the sunshine states. These are fast growing states. And there is just a plethora of inexpensive raw land. Grant Okay. All right. That's fascinating. The other thing that I think you wrote your book was in 2017, did I get the date? Right? I think 2018 and 2018. Okay, dirt rich, dirt Ranch is out on Amazon did a review of that awesome book. Tell us about that? What does that cover? Mark So Dirt Rich gives you the basics of how to buy and sell raw land, it also tells my story. So you don't make the same mistakes. I did. And then Durbridge two is coming out very soon. The next plot how to scale your business. Grant I love that the next plot, there's a play on words right there for sure. You're also out there on medium.com. I see you being referenced and talked about there. As well as you got your website, check that out as well land geek, the land geek.com, right, the Land Rover COMM And I'm assuming that is I reviewed that what I noticed about what you have here is this is where people can come to your organization, if I understand it, right and say, hey, I want to get trained in this. I want to get skilled and how to create my own business. I'm assuming this is where you take your years and years of expertise. And you condense that into a program, if you will, that take all the lessons learned rather than take 10 years to learn it. You'll learn it and you know, how long, what is sort of the up ramp for people in terms of amount of time and effort? Mark I mean, can really get going in about 16 weeks. Okay. Yeah. Grant That's, that's amazing. It's amazing. Have you do you participate in any sort of real estate investing other than raw land? Mark No, because I don't have an advantage in any other real estate niche other than raw land. So I'm a inch wide, and a mile deep. So and no one can really get my returns, it would be nice to get depreciation because land lasts forever. But that being said, I don't have to deal with the depreciation like there is depreciation for reason I don't have to deal with any physical structures. So I like the headache free piece of it. And I got it 90% automated with software and expensive virtual assistants. Grant That's incredible. So tell me about your, your best type of client that would come to you and say, hey, I want to participate in building passive income with your program. What does that look like? Who do you know? Mark You gotta have a burning desire to change your life? Right? You don't have to grit. So anything we're doing in life is inherently hard. And so it's kind of like hockey, right? People who play hockey, really love hockey, because they love it enough to get their teeth knocked out and get back up. It's the same thing in business. You have to love what you're doing enough to get knocked down and get back up. And so if you have a burning desire, give me that more than somebody who has cash. So I always say commitment over cash. It's, that's really all it takes. Grant How much cash did you have when you got started? I mean, it wasn't a ton. Right? Mark I start with $3,000. My buddy Durant's are $800. We think that, you know, 5000 is a is a really easy number. We have some clients who start with $500. Grant So you really don't need a whole lot of cash is needed that commitment or that grip that that desire to move forward with it. Okay, very good. So, any other tips that you'd want to share with our listeners on on doing this? Mark Well, if I were the listener, I would be thinking, well, Grant. It's so great. Why is Marc teaching it? Grant That's gone through my mind. I mean, You're talking Yeah. 300% To 1,000% return. Mark Right, right. So to answer the question, because when I started teaching that my wife asked me the same questions like, aren't you going to create your own competition? And it's a very valid question. So I started putting on my investment banker hat. And what's the first thing, investment banker looks at? How big is the market, and there are billions of acres of raw land available in the United States. And there is literally do you couldn't think of a more boring niche, like you could go on HGTV or the DIY Network and think, Oh, I'm gonna watch flip this land. The before pictures are all in the after pictures are all in. Plus, there's no hedge funds, there's no private equity groups. So you meet a million people can be in this niche, will all run out of money, before we run out of deal flow. Grant Plenty of opportunity for sure. So is some of this sort of altruistic in terms of you know, you want to give back, you want to see others sort of experience some of the same benefits you have is, is there a component to that that's driven yet to create these systems? Mark I mean, that really is my, my purpose, honestly, because, you know, buying and selling land is great. It's helped five people, really, my family. Yeah, that being said, nobody ever bought a piece of land for me, you know, called me and said, Mark, you changed my life with this land investment, but being able to help people retire their spouses, so they could spend more time with their children, being able to have people replace their income, and really get out of what I call so economic dependency, which means that they're personally not working. They're not making any money, so that they can move up Maslow's hierarchy of needs, into self actualization, and solve not just their money problems, but their time problems, to explore their highest purpose in life. That has been the most gratifying thing for me, professionally. And I absolutely love waking up to that idea every day. Grant This is the "why" of your journey. Right there. That last sentence, isn't it? Yeah, it's helping them to get out of that solo economic dependency for sure. You had mentioned at one point, or I saw when I was doing some reviews on you, five reasons you should be creative, Pat, you should be creating passive income in raw land. What are those five reasons? Mark The first reason is, it's just so simple. All you got is a piece of land and a buyer and a seller. So you know, juxtapose that to like, say multifamily, where you've got to raise millions of dollars, you have to get private capital, you have to get investors, you could spend a...
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CAIR 74: Invest Like The Wealthy To Change Your Life
07/26/2022
CAIR 74: Invest Like The Wealthy To Change Your Life
In this episode, I have the opportunity to talk with a self made entrepreneur who's followed the footsteps of her amazing dad, and in the journey has discovered what the tips are that the wealthy use to invest to change your life. Grant Hey, everybody, welcome to another episode of Financial investing radio. So I have been trying to track down this person multiple times and admitted it was my fault. I could not get my calendar right to meet with Stephanie Walter. So glad to have her here with me today. I'm fascinated with her background, what she's done in terms of growing wealth. But before I go any further, Stephanie, welcome. Stephanie Thank you so much for having me. I appreciate it. Grant Yes, this is fun to have you here. Your journey is a fascinating one to me, because it's this journey as I reviewed it, of gathering some financial capabilities, but then not resting on that, but rather using it to leverage for future wealth. So I don't want to give that away because I want I want our listeners to hear this cool journey that you've gone on. But let's rewind. Okay, let's uh, we won't go back to where you were raised as a kid. But let's go back to you get out of school, and you're thinking I'm gonna go do some work. And that led you down a certain path? Would you talk about that? Yeah, I did what like most people do, I got it. I just got a regular job with a corporation. Stephanie I had some interest in insurance. So I became a claims adjuster. And, and I sort of moved up the ranks pretty pretty quickly to where I was working kind of as a liaison between the attorneys in that represented the insurance companies and, and the insurance company. So that was, that was really interesting, but just, you know, working in a corporate setting, I remember that, you know, my pivotal point was I was getting a 2% Raise after my superiors had said, what a fantastic job I was. You're welcome all 2% Did you get to keep all that 2%? Or did you know you got to keep? Grant That's impressive. Yeah. Stephanie And I went home to my Dad, I just bought a house and was like, Dad, I just, you know, look at how much gets taken out. But with taxes, it was a big learning experience. I mean, well, as you know, I did put, you know, seven years into it, but just realize that, you know, if I'm making these 2% races for the rest of my life, you know, what is that going to look like? And my dad was an entrepreneur, actually, he's a second generation entrepreneur. And he's like, Well, you know, what you're gonna get if you stay in this, but if you go out on your own, you know, really what you build will be up to you. And it's your choice to do what you want to do. And I gave my my two week notice probably the next day, did you really? Oh, wow. That's okay. Wow, a woman a decision and action. That's awesome. Grant So, all right, so you gave you gave the two week notice you left, and then you didn't go to the pool? That's for sure. What did you go though? Stephanie Well, I have a I have a lot of relatives and insurance. And that's kind of how I started in doing in claims to begin with. And so I just knew, you know, the company I was really familiar with, went and signed up with them, took all the classes to become an agent and and just, you know, started started working, you know, right off the bat, state and insurance agent for about 16 years. See, I started that I'm trying to think of like timeframes, I think it was 2004. And then right around that same time, I kind of decided, you know, with the when the bottom fell out to buy some real estate, single family homes, right in an area in Denver, I'm a native, as I mentioned, where I felt like if there would be growth, from Denver that, you know, over time, these would probably be good, good investments to have. And that was in the Sloan's Lake area if people are familiar. And so I became, you know, a untrained landlord, as well as a business owner at the same time, all in one shot. So quick question. So when you did this transition out of the corporate world, into the entrepreneur going to do myself. Grant How many entrepreneur books did you read before you got started? Stephanie You know, I? I didn't read that many. Grant Yeah, that's like I could tell you just jumped in and went after it. Right? You got going on. Stephanie I think also my my step up in that area was I'd see my dad growing up who had never, who had always had businesses and so to I never saw him work a nine to five job, you know, have a two week vacation or anything like that. So I had a very good example of what an entrepreneur looks like. And so that's probably why I didn't need to read books. I have since read a lot of books. Grant But yeah, yeah. But you had a role model, you had a mentor to follow after. Alright, so you go through this journey, you run your real, or excuse me, your insurance agency for 16 years. What happened? Stephanie I mean, as time went on, there was you know, also some distaff dissatisfaction. Because you, you know, you really like your clients, and they're doing business because of you. But then there's this big, you know, corporation behind you, mine was Farmers Insurance, who, you know, ultimately makes the decisions based on, you know, the claims and the the rate changes and things like that. So that became kind of frustrating. But then also, you know, again, my dad was, you know, pretty. He passed away, actually, shortly after I started my agency, but I'm sorry, yeah, thank you. But I had, I remembered a lot of things as time went on. I was like, Oh, I remember when Dad said that. And one of the things he always said was, don't put all your eggs in one basket. And that was for me, that meant just, you know, don't continue, farmers was very big on, take a loan out, to keep running your visit business, make it bigger, make it better, all these things, where I just sort of directed my money in my growth into real estate, because I felt like it wasn't so attached to to the business. And I loved real estate. I didn't know much about it. I certainly wasn't very educated about it. Oh, I think it was 2016 I had gotten an invitation to a boot camp and about buying apartments, which I had always been curious about, oh, cool. Went into there. And that's where I first heard the term syndication. And I was I was just blown away, I'd never heard that I loved the idea of a group of people buying something that no one could do on their own. And I from that point on, I was all in there. I did about three years thing me maybe it was only No, I think it was only two years of education, which, you know, was an investment, but you come out of that bait being able to be very knowledgeable about commercial real estate, which is very different than residential real estate residential. Grant So if I hear you, right, I think you said that this transition to real estate, it was a diversification strategy for you following your dad's counsel, right not to have all your eggs in one basket. You still had the insurance company at least for a while, right? And then then you started investing in the real estate, is that right? Stephanie Yeah. i And well, I had all I had invested, you know, in the single family homes and they're, you know, through the last crash and then wanted to do the apartments and then in 2016, that really was probably, I mean, I kept running my agency obviously, until actually last year when I Um, my investing had my income from investing had exceeded my, my business income. So I was able to retire, or in my case, just do do a different career for a while. Grant I love that when I saw that in your profile, I thought that was the ultimate, which was to sort of break away. It's that, hey, I'm no longer just going to be a business sort of operator, right? I'm actually going to step aside and let let your income or your assets generate that income for you, right. It's the money's working for you. And I saw that in your notes too, which was a, you said some interesting about the way the wealthy do it, which is the wealthy have their money working for them? Was that always at the forefront of your mind? Or did you sort of discover that along the way? Stephanie No, that's a that's a big, I think it was big, the aha moment for me. And how I describe it is that I believe most people, and I was one of those most people believed in an accumulation model of money, which meant for most people is I'm going to accumulate the money in my 401k. I never really, you know, went down that path from owning my own business, I wanted to accumulate my money in real estate. But yet my idea was the same, which is I'm going to buy this property and manage it for 30 years until the loan is paid off. And then I will live off of the rents or whatever at that time. But when I started raising money for the syndications, I started becoming friends and, you know, meeting really, very interesting, you know, wealthy people, and just notice that they were doing stuff differently than than I was, I couldn't quite put my finger on it. But after a while of working with them, I realized that they look at their money as a good word is utilization. They're always using their money. They're using their money to give them cash flow. And there was kind of the light bulb that came on for me. Later on. You know, I started doing syndications in 2018, and I think it was the end of 2019 that I started to sell my properties one by one, and invest them in syndications. Because I realized I had these this great big chunk just sitting in and it's really not doing much as far as you know, cash flow, helping me out at all. Whereas, you know, if I just shifted my focus and where I put my money, the returns as far as cash flow, were really significant. Yeah, Major. Grant Have you ever played that game called cashflow there? I've heard about the Robert Kiyosaki Robert Kiyosaki game. Yeah, I've never played it, you shouldn't play I have a feeling you do really well with it. Stephanie Yeah. Grant Excellent with cash flow is king, as you're as you're pointing out, and the ability to get that cash flow lined up and consistently look at money as a tool to deliver the cash flow is critical. So that 401k experience, I've had that same journey where I was putting money I was putting money in in a 401k. And then the first time the market in my career, you know, did this massive dive down, right, and I'm sitting there thinking, I know that there's someone on Wall Street's buying puts against my investment making a ton of money while I'm losing a ton, wait, who came up with this strategy, right? You know, also you could keep your you know, 2% Raise, it is it is a disservice to the working class for sure. So, did you did you ever get involved in the 401k strategy? Or, or did you ultimately just leave it wouldn't? What happened there? Stephanie Eight, actually, I have my series six, when to be a n 63. So for the audience, that just means that I was registered to sell products, you know, mutual funds and things like that to my database of clients. I never really like to that I never really, I felt the variability and that the training that I was given never seemed to give me a lot of anxiety. And so I never really did much with that. And inevitably let those those licenses go. But though the 401k Actually, I'm in the process of writing a book and there's going to be there's one chapter that's dedicated to the 401k, which I do a great deal, you know of research on and you you pit. You know some really good points on on that. And but it's just letting people question it because there are so many things about the 401 K that are, you know, you're giving you're giving your money to someone else to watch. And they're not doing it for free. And financial institutions want to hold on to your money for as long as they can and give it back, as you know, little as they can. And so you're you're using your money to subsidize things that you probably don't even know your money's doing. And I know, these are hard things to come to in this day and age when it's just like, can I just give my money to this person and have him manage it? Or have the 401k make those decisions? Why do I have to be involved with everything, it really is a significant amount of money that you pay to these financial institutions. And you can do much better on your own. But I won't go into that. That's a whole nother discussion. Grant That but that's your journey, though. I think your journey is you figured out Wait a minute, I can do something differently with this. And you took control of it right? You did the education you put in the work, you discovered cash flows. The secret to this, let my money work on just building even small incremental cash flow growth and how critical that is in the strategy. Stephanie One other point just quickly is I was watching something on TV last night, and there was several commercials that came on. And they were women. They were geared to women and there they were talking about, you know, women and finances are bad with finances. And the whole message in this commercial was save your money for retirement or whatever. And I was like, I want to just get out the message that it's not saving your money. It's investing your money and learn how to be a good investor, because those are the things that are going to allow you to retire early or retire in not a poverty situation. But in you know, invest and learn how to invest because it isn't as hard as people think it is, you know? Grant Yeah, absolutely. I love that and are good. I understand. You're right. Did you say the messaging in that TV ad was that women are bad with finances? Is that what you say? Stephanie Yeah, I think well, they were trying to you know, women were kind of trying to empower themselves by saying, I'm not bad with finances, even though you know, I've been told that women are bad with finances, but it seemed like the solution for them in that commercial was save. Save your money. You say? Like, no, no, no. Yeah. Yeah. Ah, good. Good. Debt should produce cashflow. Right. That's, that's actually that's actually the message right there. One of the things I noticed as I was looking at your background, and the things you've done, as you had made a comment if I if I've got this right. Grant Money myths, you talked about money myths, and I think you just touched on one of those. What other money myths? Have you learned that we hold on to that? Are these incorrect notions that actually hurt us financially? What have you found? Stephanie There's one very significant one, which is people will say, well, the wealthy people, you know, I've talked to people and they'll be like, Oh, but the reason the people you work with have so much money is because they're willing to take these crazy risks with their money, and stuff like that high risks. That's that's why they got where they are, they are and I say actually, nothing could be further from the truth. The majority of wealthy people invest in extremely conservative things. They, the other myth is, you know, put put your money into the stock market. Many people can't tell you in their mutual funds, what they're invested in, what even one company is that they're invested in, let alone who's who are the team members on that, you know, on board or who's the CEO of the company, they can't tell you anything. Whereas wealthy people they tend to invest if they do invest in businesses, they invest directly in a business, either for themselves or they understand the dynamics of the business and the business plan and they invest that way. If they invest in real estate, they largely do the syndications and they get to know the team that's running, running the syndication. They know what kind of experience they have, what kind of past returns they've done. They do their homework in that sense. But then once they've invested in the team, they tend to invest again and again. And these are very conservative things that they're investing in things that are tangible in value. That's another. That's right. Three things I'm hitting is wealthy people tend to invest in things that have tangible value, which means, you know, an apartment complex Well, let's say, for some reason, it's terribly mismanaged and it goes out of nobody wants to be in it anymore. Well, you still have the building and the land in which you can sell. So there's, there's tangible value there. Grant Okay, so the tangible piece, that's interesting, too, especially in today's world, where digital assets are becoming more and more of a thing, right. In fact, I saw recently, someone talking about digital real estate on one of the online ads, you know, doesn't feel tangible, right. Are all the NFT stuff going on? Right are the crypto so many intangibles today as well? It Do you have any position or thoughts when they do that? Stephanie I don't because I guess I always take the line if I if I don't understand it, or if it's not something that I want, you know, I guess it comes down to really understanding it. I've had a lot of people explain it to me, but I still don't, you know, the ups and downs, you know, lately, it's been a pretty big crash, you know, people are saying that's a good thing. Okay, I still don't really understand it. And I know that they're planning on, you know, digitizing, then that's, that's probably, you know, not too far away in real estate, you know, 10, I would hope it's going to be 1015 years in the future. I don't know what that looks like. But that's definitely something in the future. I don't think that is wrong. And when I say that the wealthy people invest in, they probably do have some investments in cryptocurrency, but that's probably less than 5% of their portfolio. Great majority of what they're invested in, probably 30% Every year. If you go on to the name of this group is called Tiger 21. And it's, it's for wealthy, wealthy people, I think they have to show a net worth of at least five or $10 million to get in the group. But every year, by agreeing to be in this group, they agreed to release as a group, kind of a asset allocation of all of their investments, and every year, there doesn't change that much. And over 30% is in real estate. Grant Really. Okay. All right. That's interesting. That's fascinating. One of the things that I noticed as I looked at it now Now the name your company, you're gonna have to help me because is it Erbe Wealth? This Erbe? Stephanie Well, Erbe Wealth, okay, everybody. Well, thank you Erbe Wealth. Grant Well, so I'm on your site, I was on your site. And I was checking out. This is really cool. . And I went to the about page and told my listeners, you should check this out. Stephanie's got this thing called the 15% Plus community. Can you talk about that? Stephanie Yeah, well, I mean, my partner and I started working together in 2018. And we both realized, as many successful pairings go is that he had some skills in in this in the certain areas, and I had skills in certain areas. And together, we have really done very well together, and we just closed on our 12th deal about two weeks ago. And every single deal that we put together has returned over 15%. But truthfully, every every one that we've done up to this point has returned over 20%. So the person designing my website said, I don't know you might want to just put that down to 15%. But every deal that we have done has had an annualized rate of return of over 20%. So if you're we, our goal is when we hold the money for three to four years, then we'll double your investment in that time. And we have we've done that successfully, and we have a system and we're will we're continuing with it. Grant That's amazing and that's that's leveraging the syndicated real estate strategy. Stephanie...
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CAIR 73: The Secret to Creating a Passive Income As A W2 Employee !!
07/26/2022
CAIR 73: The Secret to Creating a Passive Income As A W2 Employee !!
In this episode, I have the opportunity to sit down with Christopher Nelson. A technology executive out of Silicon Valley who's figured out the secrets to helping you achieve passive income as a W-2 employee. Grant Hey, everybody, welcome to another episode of Financial Investing Radio. So today I have in the house with me, Mr. Dr. Why don't want to call you. Sophisticated, brilliant. Christopher Nelson is in the house here with me today. I love his subtitles technology executive real estate investor, author, podcast hosts and inventor of the space station. Was that right? Or did I get that right? Christopher I think you may have stretched on the space station. But I you know, space has always been a dream of mine. Right? I am a low tech tech technologist, a bit of a geek. So yes. You can learn more here: Grant Excellent. Excellent. Well, okay, so let's start with that. technologist geek. What does that mean? What? Tell me about your background? Christopher Yeah. So So my background, you know, interestingly enough, I started with just a love of technology, right? You know, I heard some people tell stories, the other day of how I think exploring and wanting to take apart, you know, televisions and, you know, anything remote controls, understand how they worked. And I just was fascinated, especially as the computer age started taking off. What can we do with these? So, you know, my thought was, I wanted to go to university and I wanted to learn how to become a software engineer, so studied very hard. And then when I went to my first internship junior year, with a large database company, and I was by myself working on this code, I started going crazy. I started thinking, what am I going to do? Like, I, I love this, I do not like this. And it was actually in a job fair that I met somebody who, who had a similar major who was working in technology consulting, he said, Hey, there's different things. It's not all you have to be a software engineer, I solve difficult technical problems with people moving businesses forward. And so that really, I mean, hit a lot of cylinders for me and took me off into technology, consulting, which is where I started my career. Grant That's awesome. I love that background. i It's funny, I didn't know that about you. I had a similar journey. I come through the technology world. But I ended up bouncing from doing my first startup right out of college. Because when you come out of college, I don't know if you know this, but you typically have all the answers, right? So so I jumped, I jumped right into startup, I'm gonna go solve these world problems. Clearly, everyone's having struggle with course, I failed miserably on my first startup. So then I jumped into the technology consulting world with back then one of the big six, you know, in Chicago doing some technology work. But yeah, it's funny, I jumped to the people side of it, also. And that, that was liberating for me, because if I spent all the time just and I love I still code today, don't tell anybody. But I use it as a tool to keep my brain active. But if I had to read every day, all day, I think I'd go crazy. Christopher Right? And, you know, it's, I actually tried to now actually take that message to people, kids graduating from college is the fact that you can actually be involved with technology. And it doesn't have to be this one way like we see, you know, again, media, movies presents this one view, but there's a lot of other things that you can do. And I found that it was great start to my career, to really get me launched. Give me a ton of skills. Give me a great background, because I did I went to work for Accenture, right that came out of one of the you know, the big six became the big four. Yeah, it was, you know, one of the big four back in the day. Well, well, we're constant names. Grant Yeah, I did. KPMG. So there you go. Yeah, technology. There we go. Wow. Okay, which office were you located? Where were you? Christopher At San Francisco. I mean, I felt like that was a great opportunity because I while I was doing the tech consulting thing I did want to work for high tech, like I wanted to work for companies that were really, you know, moving the needle. And that's actually set me up. So about eight, nine years into my career, I realized that I had this great experience. And this is what I call in my book, Your career capital, which is a combination of your education, your experience and results. And I realized I could actually go trade this for equity in startup companies, because like you said, I've been working for these tech consulting companies, I got that figured out, right? Well, I went to work for my first startup, abject failure, right, I found myself and then a year nursing and Ulster having a bad boss. And I didn't know how I got there. But taking a step back, and I think a lot of us figure out pass through failure. And so I don't think we should fear that. And I realized I did not look like I did not think like an investor with my time. Like I'd been, you know, in the in the stock market investing since, you know, the 90s. But I had not thought like an investor with my time. So went back, put together a due diligence criteria started work in my network, what did people recommend? The next company I chose employee for 17, at a company called Splunk, in 2011, and up IPO in 2012, and it turned out to be a big win for my family. Grant Yeah, that's absolutely cool. Yeah, Splunk, boy, they have done a great thing for the industry. It's funny, united, similar routes, I, after I did my KPMG route for a number of years, I had this itch to get out to Silicon Valley. And so I was chatting with this startup company out there. And, and I said, my wife, you know, I'm just gonna fly out, you know, we're in Chicago, the time's gonna fly I just checked, probably won't do this, right. Uh, probably, but I just gotta go check them out. And of course, I get in there. I'm talking with them. And after several hours of whiteboarding and brain, brain exciting things, they go, do you want to, you know, come join us? And I'm like, Oh, I think the answer is yes. You know, and I remember being on the phone in the little conference. You know, maybe my mind's changed. You know, I think we're switching. We're moving out here. Yeah, I did several startups out there as well. And those course weren't much different. So you know, you need to have that first one that kicks you in the teeth, right? And it's like, okay, wait a minute. You do, you do? Christopher And I think sometimes, right? It is, you know, those those learnings that help like anything else, right? I mean, this is where I'm trying to now build this thesis and conversation around, it's an investment of your time. So sometimes you go, you get skin in the game, and it's not the right thing. But then does that mean you stop investing altogether? No, you go and adjust your lens and you you go, and you get feedback, and then you go, and you do it again. And maybe this time you say, I'm just gonna, in my head, I may sign a four year contract, maybe let me just do two years, see what's there and track it as they go along. You're going to also be looking at those quarterly meetings, when they're giving readouts a lot differently, you're going to look at the market a lot differently and say, What can I do with my time? Grant So I think that's one of the cool things that I noticed about you when I was reviewing your profile. And it was this, it was not just let me go after doing this startup. But it was to leverage what I'm getting out of this either equity opportunities, but to move it into some passive opportunities. And I think that was, for me a real Aha, like, you know, earlier in my career, I wasn't even thinking that right? I'm doing the various startup companies. I'm like, go, go, go, go go. And you think you've got all this endless energy. And at some point, you think that way, but what I love is a year connecting the dots from take that energy and translate it into this passive mechanism that's going to benefit you. So I don't want to steal your thunder. But talk more about... Christopher Well, well, what led me to that is it was actually that first IPO. So all of a sudden, you know, I'll never forget that day was you know, April 18 2012. Phenomenal day. And but the most memorable moment wasn't this big party, the fact that it went out double what we thought it was, was when I went home that night, my pregnant wife is sitting there, she asked me two questions. She says, When can we get the money and when can we buy the house? And I had no answers. And I literally went into the next room and started emotionally, you know, falling apart a little What I didn't realize is I was experiencing what's called a sudden wealth event, which is sudden wealth syndrome, which is a psychological syndrome that when you have these things you feel lonely, depressed, stressed out. If you're not prepared. You're not and I wasn't like I'd fought so hard to get there like most of us do. I wasn't prepared aired in so what I found grant is that many people aren't prepared like they like and I literally have been interviewing a lot of people from my book a lot of technology in place. And they will. I heard Mark Cuban say like you have to work for equity if you want to get ahead or, you know, I heard Gary Vee or somebody, Robert Kiyosaki gives them the idea that they want to be an owner. They go get it, and then that's it. They stop. And so my experience was okay, now we got this. I was okay. How do we now start getting this? You know, because I was tired during the six month lockout period, over 90% of your wealth and a single stock. I'm telling you, man, like I ate a ton of Tom's during that time, like you do. Yeah. Yeah. So it was really been this plan of, you know, how do we start moving it into something passive? How do we get it to that, you know, Kiyosaki goal. And so as we were doing that, as we were, you know, scouring the earth in the Bay Area, trying to understand it, we started getting exposed to real estate syndications, we started getting exposed to crowdfunding. And we realized that we had to get sharp on the math, we need to really understand how to do diligence, how to, how to invest. And, you know, we went on a journey of where we figured out how to start getting some skin in the game that, you know, was something that we could afford that we could afford to lose, and start really understanding those types of investments. And as we started seeing more and more success, other people started raising their hands, because we were very excited, we would talk about what we're doing. We always feel, you know, with our children with our friends, we should talk about careers and money. Like we should just have the conversation in an appropriate way. Not in a braggadocious way. But in a What are you doing? What are we doing? Because if we don't talk about it, you know, like you do here? Yeah, we don't do anything is people who sit on it. Yeah. Yeah. Grant You do, you do sit on it. Absolutely. So. So tell me about I think I saw something that you wrote. "From No Dough to IPO". I love that. Christopher Yeah. And so this is, this is the first book that I'm writing. And it's really going to be a playbook on how to tech employees think like an investor when trading their time and talent for equity. Right. And I want it you know, you said it grant like, nobody gave us the playbook. Right, we had to go in there. And we had a trip over our own shoelaces, you know, get beat up, figure this thing out. I you know, I have interviewed people in my network who have done three or four IPOs serially, I've interviewed people that have never done anything pre they've all been in post companies, and they get these companies public, and they take them from, you know, 500 million to a couple billion dollars. And they've gotten tremendous wealth, already liquid the whole time. And I've turned it around and put it into a framework so that w two employees can really be time investors and say, you know, for myself, I had lost a small business. That was my side hustle, I was broke in, I realized I had to go and work for startup companies if I wanted to get ahead. And I think many people are trying to figure out, how do they leverage their skills, their time and their talent to do that? I wanted to put it out into a book that says, here's how you actually set yourself up. Here's how you negotiate for the equity. And then once you get it, what do you do you need to plan protect, and then you need to start producing passive income. Grant So that framework that you've alluded to, and obviously it's in your book and what it is that you provide in terms of services to others? Sure. In that framework, how far does your organization get involved in terms of taking people through that and applying it as a good go all the way through into the real estate piece itself? Or tell me more about that? Christopher Well, so I mean, the book is really launching the education platform. So right now the book is really the key anchor, we are looking to follow with some online training that people can do. And we're considering some coaching programs. But yeah, I mean, getting back to the origin story is that this this endeavor started from us doing done for you investments for technology employees, my wife and I who were actively investing in, you know, multifamily in ATMs and mobile home parks. We were asked by our friends to help start creating some vehicles for them because they wanted the success they didn't want to go put it together. So that's how Welford capital was born five years ago was in in an effort to help technology employees and you know, we're the lead investor, we're leading with our families dollars, we're creating a model portfolio that's based on where we've taken our tech equity and how now we've put it to work in real estate with our my wife and I shared goal the goal of getting to $300,000 of passive income a year. Grant Yeah, that's awesome to get to that. Point, what's the trajectory? Like? And I? I'm sure part of the answer is how much you're putting into it financially. But in order to in order for someone to get to some, I guess what I would call, in fact, I was watching on your YouTube channel use an interesting phrase I'm looking at right here. It was something like, yeah, you wanted to get to a point where your passive income could overcome your W two income, you made that video. So I realized that's gonna vary by person. But yeah, sure range like, Is it A, is that a two year or five year journey? What does that look like? Christopher Well, I think to your point, Grant, it depends on, you know, how much you can deploy, I really think that it is a five year plus journey. For most people, I think that if you have if you're sitting on a ton of dry powder, right, if you've had, you know, a couple of exits, you know, still it's gonna take time to deploy that capital. Right. And this is what I tell people is, if you walked in, you know, with $10 million, you would not want to put that into a single real estate investment, because then you're going to have the same thing you should if you're sitting in the single tech stock, you're gonna be not diversified. Right? So I think on average, it's, it's, it's a five year journey to really start making some impact. And this is why, you know, I want to go upstream to people earlier in their careers thinking about it, because my honest belief is that if I can free technology employees from having to work for a W two, many of them still want to make an impact. And this is the conversation I love having is if you didn't have to work for money, what would you do? You know, eight out of 10 tech employees don't say I'm gonna go travel the world, they'd be like, I want to solve this problem, or I want to fix that problem. And that, to me, is is really powerful in our community, right, as a technology employees is how can we unleash that power, and allow people to do the impact work and not be focusing just on the survival work? Grant So I have a fundamental question for you, when I saw that your focus was on the tech space employee. I'm assuming this could apply to any sort of w two employee? Or is there something about what you're doing that says, This is really relevant to a tech space employee? Christopher Well, so the reality is, is, you know, I want to be able to speak into my people, my focus, my niche is focused on technology employees that I really understand, I understand, you know, their concerns, I understand, you know, you know, how it is, it's a very high paced, fast paced lifestyle. And so, in. So that's where, like, my writing my books, and everything is very much focused on how do I help these people and try and pay it forward, if you will. Now, on the real estate side, it's interesting that I've been very focused on technology and plays in helping them however, different people relate to the story, right? I mean, I have people that come in and say, Oh, I've I've gotten equity, it hasn't been in tech. Can I invest with you? Of course, you can, you know, or, interestingly enough, I had a jockey that reached out and wanted to get a call and said, I actually won this big stakes race. That was my big one. And I went through the sudden wealth event, I really related to what you were talking about that, can I invest with you? And so of course, I'm open to everyone participating in our investments, but I just feel really nobody feels sorry for somebody who goes through the sudden wealth event, right, you know, works in an IPO, all of a sudden, you get a multiple seven figure, payday, nobody feels sorry for them. But those people still struggle. A lot of us, myself included, didn't come from money, had no idea what to do with it. Yeah. Right. And so it's really, you know, in my mind that I want to really help and lean back into my community, because as I mentioned before, like I think that that community, financially independent will actually then turn around and bring some huge benefits to to everybody. Grant I can relate with that, I grew up milking cows and hauling hay. So yeah, that was that was that was the foundation of that. So I'm interested in your thoughts around because one of the cool things I saw that you did was you're helping people think through their career paths, and with everything that's taken place with COVID and the impact to the workforce and and even what people are expecting from their jobs today and how that changed. The mindsets changed. How is that impacting the things that you're doing? Christopher Well, I think it's creating more opportunities, right? I think coming post COVID I mean, it was in the middle of COVID. I ended up going back to work for another technology company. I had a very interesting offer. And it was for an all remote company that was built all remote they came it was developed all remote in 2011. And it had an An amazing trajectory and amazing story. And it was important for me to really experienced that because I think that the future of technology employment, while I know a lot of people are being brought back into the office, I think it will truly, ultimately become hybrid, that where you're going to have office time to connect, you're going to have a lot of home time. What this allows for, you know, I think certain roles, certain specialized roles is the ability to make tech money and live in the low cost, you know, income or a low cost of living areas. Yeah, that wouldn't change. It is in this to me provides opportunity to what to save more to invest more, right? There's this whole concept of people talk about lifestyle by design, well, what if you designed your lifestyle to invest more, and I mean, this is what, you know, really motivated us to leave the Bay Area, come to Austin, Texas, in 2017, where, at that...
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CAIR 72: Tax Saving Secrets From An Insider
06/30/2022
CAIR 72: Tax Saving Secrets From An Insider
In this episode, I have the opportunity to sit down with someone that has digested and synthesize the tax code and brings the tax saving secrets to you. Grant Hey, everybody, welcome to another episode of Financial investing radio. So today I have with me someone that just barely met. But as I review, his biography, his profile what he does, it is in one of those places, which I admittedly know so little about, I lean on so many people for help in this area. Now I get to meet with and speak with an expert in the area of how to take it to the tax man. All right, let me welcome Mark Meyers here today. Welcome, Mark. Mark Hey, thank you so much, Grant, I'm excited to chat with you about this. And, you know, hey, if you can keep more of that hard earned profit. It definitely helps in the wealth accumulation realm for sure. So this exciting topic. Grant Boy, for sure. You know, when when you think about taxes and talking about taxes, you know, it's probably right up there with flossing your teeth, right? It's like, oh, everyone should be doing it. Right. But oh, my gosh, do I really want to talk about taxes. Turns out, as I was reviewing some things that you have done to help people, individuals, businesses, really reduce their tax burden. And putting that money, like you said, or leaving that money back in your pocket, suddenly, it becomes really an interesting topic to address. But before you give away any secrets, let's back up. How is it that you got interested in taxes? What is it that even got you to this point? Mark Grant, you know, it's an interesting story, because I started out my career at the University of Florida, with as an undergrad in exercise physiology, get my Master's in sports management, moved to New York City to manage health clubs, and then moved to Los Angeles to edit, manage more health clubs. And in the process of doing that, I helped a really large high end brand, open a number of different locations. And in that they were they went from a 10 clubs to over 100 clubs. And in that process, I really learn to be an owner operator, every club that I would open or go chant, you know, help return around, I'd have to really be mindful of driving revenue, minimizing expenses, putting the operations in in place, you know, the best practices in place to get the best output. And of course, I was compensated on EBIT margin, so I'd get a base, and then I'd have cash bonus based off of how profitable is the company process, I realized, you know, hey, I might be running health clubs. And I might have a background here, but I have a knack for running companies. And I know there's a lot more opportunity in the financial markets in the financial world, particular to consulting with business owners, that's when I said the light came on after, you know, working well over a decade, you know, 365 days a year, and these clubs are open from, you know, five in the morning till 12 At night, you know, they never got hit. So I'm like, Okay, I'm going to shift gears here and do something fun that can ultimately help other people, and also helped me kind of increase my income opportunity here. Get out of this glass ceiling environment. Grant Yeah. So So you are living this life of just constantly being on right, the lights on, right, because your clubs are on right, the gyms are open, and so you're trying to optimize as much as possible. Talk about school, hard knocks, right? I mean, you learn the lessons along the way, for sure, right? Oh, for sure. Mark I mean, it's one of those things where you know, every penny counts, particularly in that industry. And of course, I worked in a higher end layer. So it was, you know, we're looking at 200 plus dollar a month memberships with spa packages and training and Pilates and Yoga. But at the same time, you still have to be mindful of your margins. That's really, really important. So it was it was a nice experience. It was a nice way to understand how to really learn the p&l, learn the people, learn the drivers, and then of course transitioned over to say, hey, I can speak to business owners, I could speak to those that are looking to, you know, increase efficiency. And there's a lot of opportunity there. So that's kind of where this all kicked off. Grant So in the course of doing this, you start uncovering, I'm assuming, oh, here's a little secret about how I could save a little more money or take some out of the taxes. I imagine over a period of time you started to build up this cadre, or list of or selection of wait, here's some best practices of actually taking the tax back from the tax man and leaving it with you. There's it was it was it that it was a 10 year journey that you invested in to build up that knowledge base? It sounds like, Right? Mark Absolutely. And you know, you really said something important, and it was very accurate in that my, my getting to where I am now didn't happen overnight. In particularly shifting gears, I'd say the last seven or eight years is when I really really shifted gears, to not just talk about can I just not consult with with individuals on their businesses and help them with maybe some financial planning, really shifting gears and saying, hey, there are a lot of different opportunities to reduce tax. And I just went out there. And just like in the past, in my first few years of this, I was kind of more of an advanced insurance specialist and consultant to business owners, and I could go out there and work with any insurance carrier. And I could basically look and say, you know, this is the carrier need for this solution. And this is why this is I realized I could do the same thing in the tax realm, there's just not 100 different, you know, tax savings providers out there, there's probably about 20 to 30 that you want to do business with. And these are small groups are generally fairly boutique, they're not huge. And they offer something very, very specific. And it's somewhere in the 70,000 pages of tax code. And they just so happened to analyze it, apply it. And basically, that's their gig key. So I have a lot of different tools in the tool chest, I have a lot of different relationships with groups that do these things. And I break when I do consulting work, I just put all the pieces of the puzzle together. And it's really cool. I'm not a CPA, I'm not a tax attorney, I'm really literally I call myself a tax savings architect, I've just developed this ability to consult, oh, that's a great title. Grant Wait, say that title again, you're a what? Mark A tax savings architect, Oh, I love it together, I just build I build the plan. And then I bring the vendors in, right, the right team on the on the coach, I'm bringing the right team in to put the right plays in at the right times. And then the implementation goes, you know, off, you know, from there. Grant So, what I want to highlight is you have developed this by doing it again and again, maybe making a mistake fixing it again and again, oh, learning more again, and you put in that 10 year effort to gather and build that experience and that that's the value platform that you bring to the people so they're not off doing 10 years of learning the lessons, right? Mark Oh, for sure. Grant, I'll tell you, these are types of things that, you know, people don't have time, even the best CPAs right. And you can think about any CPA out there, you've got out of every 10 You're gonna have to my experience, you're gonna have two out of 10 that have developed their practice in a way that they'll have forward looking have a forward looking approach. And they'll have more bandwidth than just, you know, recording and tracking and filing right most of them record track and file. Do you have any more expenses? Are you sure you don't have any more you know, you can buy this capital, we get section 179 it so why don't you spend $1 to save 35 cents? No, that's, that's really a good idea if you need what you're buying. But two out of 10 are forward looking right? They're actually stepping outside of the box and seeing what's out there. They're 70,000 pages of tax code. So this is where the key is at 10 years, you're talking about their 70,000 pages of tax code you if you're going to win a championship. If you're a team think about a just a collegiate team or a professional team. They have multiple coaches. They have strength coaches, they have quarterback coaches that are talking about football they have offensive line coaches defensive line coaches look at businesses the reason why Amazon and Microsoft and General Electric and Nike and DuPont the reason why they pay significantly lower taxes than the average individual is because they have teams they have accounting teams, more than one CPA, they have attorneys they have business strategists. So this is what I really do is I bring that team approach to the small to medium size business owner or you don't even have to be a small to medium sized business owner to have tax savings you can be a high income earning executive. Oh really how to Matt navigate the tax code. There's things that you can do to reduce your tax. Grant Okay, so that gets the the question I was gonna ask around who is this for? Definitely the business owner. But if you're, if you're in the High Net Worth areas and individual this is applicable to you as well. Mark Absolutely. There's three there's three He kind of avenues, business owners. And the reason why is business owners are great to work with because they have control over their income, they can determine how much salary they take, they can determine how they take their income. It really they have the control. The other side would be high income earning executives that maybe don't have as much control but they're they're looking at, you know, half a million dollars or more of taxable income per year. I can work with business owners with much less I mean, they can have as low as 250 or so in taxable income, okay, because the more there's more flexibility. And then the Third Avenue is people that are selling highly appreciated assets, once a lot of crypto traders or somebody that had a stock portfolio, but they didn't have this huge blend, it wasn't like a qualified account, it was just a brokerage account, they had positions that just blew up, and now they're sitting on, you know, $5 million with Apple stock. Well, if they pull the trigger on it, they're looking at, you know, if they're California 37%. Grant Yeah, goodbye to that. Mark Yeah, well, I can help them, you know, really take care of that as well either eliminated or different depending on what solutions we're looking at. Grant So, okay, what about what about on the, on the inheritance side, same same sort of story. In other words, let's say you inherited something is you have techniques that helps with that group as well. Mark Well, on the inheritance side, I don't spend a lot of time there, because generally, that should be done prior to and a lot of the work that I do actually blends in with maybe some estate planning attorneys, because you really want to solve that equation prior to the need. If you don't, then unfortunately, if you're above the exemption rate, the estate tax man will come take, you know, 60% of that from your kids, right? Not from you, but from your kids and your loved ones. And they might even have to be, they might have to sell appreciate it like this is a real estate high net worth real estate holder, they're selling off real estate just to pay the estate tax, which is never a good thing. So we when it comes to the gifting and the you know passing on to heirs, we generally integrate that into our planning, but we're doing it prior to so that way the kids and their loved ones can breathe, you know, sleep well at night and not have to worry too much about worrying too much about about that sort of thing. Grant So so let's take the scenario of you're a small and medium business owner and you've got the you've got this tax burden on you. Do you need to be doing the work ahead of time? Is this a whole year of effort that the business owner goes through? Whether they have to be intentional throughout the whole year? Or do your practices, techniques allow you to just sort of come in at the last minute and who 30% off? Thanks, Mark. Have a great year? Mark Yes, well, I would say a little bit of all apply. But proactive forward looking is always the best. The best approach is a forward looking approach. Now I can do hindsight foresight, and then give you insight. On the hindsight we're always looking at, well, what did you miss that you can go back and pick up a lot of people don't realize, particularly in business, there's tax credits that they can pick up in previous years. Currently, right now for the next few months. There's the employee retention tax credit. So there's there's r&d credits, there's there's trends for investing in renewable energy, they can go backwards and pick up previous taxes paid, it's always look at the hindsight, what can we pick up that you paid in the last year or two or three? Ford, Ford sight? Or, you know, foresight is okay, what can we do to change the trajectory of your current income? Because right now, the way we're always looking at pathways, how are you taking your income, because what we need to do is look at creating new pathways. And if you have different pathways to receive the same income, there might be a different taxable situation. But those pathways aren't going to save you. You can't save any money until the pathway is created. So the foresight we're always looking at, well, this is how much money you're taking in now. And you've taken it in one pathway, or maybe two pathways, and this is your taxable outcome. But what if we created two additional pathways? Now you have four pathways, and we're not talking about deferring it. And putting into qualified accounts. I'm not talking about any of that, obviously, that's been going on for years and years and years is there's arguments as to whether or not that really is saving them anything. At the end of the day, we're talking about really taking tax law and the tax code by the horns and saying, hey, the tax code says I can do this, therefore, this money is not taxable. Right. So now that you have this money in your hand, that's not taxable you and you've lowered your adjusted gross income because you took a portion of your money that the tax code says is not taxable because of the way that you've structured it structure that we've just just decreased your taxes and you're like liquid, like the money that you save is liquid, it's in your pocket. If you want to use that for investing you can if you want to use that to recapitalize your business you can if you want to use that to go to Vegas, you can. Grant Yeah, your choice and that's the whole point. It's your choice rather than Uncle Sam. So the strategy seems to be tell me if I've got this right. It's don't fire your CPA because you're going to keep The CPA as a business owner, because you're not the CPA, but what you are bringing is a way to be more productive as you work with the CPA, right, you're bringing in additional knowledge or insight that will then be brought into those conversations with the CPA currently have is that close 100%. Mark And what I always like to tell business owners, and right off the bat is, you know, let's, let's not put your CPA on defense mode, right? They, there's no CPA out there that has the bandwidth, to have this time to vet and research all these different ways to save taxes. I mean, they know a lot, but because they may not know everything that I'll bring to the table, that's okay. So the first thing is make sure that they're not on the defense. And also, I'm not looking to take over any bookkeeping, your tax filing or tax prep, I'm just looking to add additional layers that usually increase revenue for the accounting because it usually does increase their need to maybe have an additional filing each year, or maybe some additional bookkeeping to take to oversee these new solutions. Grant So it's all day for you as a partner in it, your they don't see you as Oh, I'm here taking business from 100%. Mark Most of the time, when I'm speaking to the right CPAs. And I'm introduced to them by the taxpayer, I get introduced to three or four new clients that the CPA has, because they're like, this is great, I have you know, four or five, or depending on the CPA, they might work with a higher net worth individuals, they might have more, but I like those relationships, because they open the door for more opportunity. Now, I will say there's going to be out of that regard every 10 CPAs, there's two that are for thinking. And there's eight that are really just doing the numbers really doing the prep the recording and filing and prepping. Sometimes the eight, there could be some resistance there. And it's it's, it's only because they don't know what they don't know. So in those situations, hey, I always say it's up to you. It's up to the taxpayer, that you're the decision maker, the CPA is not the decision maker. And I have you know, I never want to pry someone away from their CPA, but if they really liked what I'm talking about under CPAs, just very resistant, doing anything that they're outside of their norm was to have dozens and dozens of CPAs all over the nation that would be very happy to interview you. Or you could interview them because they know the solutions and their clients use them. Grant Yeah, I was gonna ask you. So how does you know? What's some guidance for our listeners on? How do you pick? How do you find those two out of the 10? CPAs? Right? What are some of the key things that someone's looking for? to vet your CPA or while you're searching for someone to say, now you're you're part of the 80%? It's you you're actually not going to help me as much I'm looking for the 20% What What are some tips you have? Mark Yeah, first thing Grant is ask them if they do quarterly meetings. If the CPA or the tax preparer for you is not meeting with you quarterly, they are not forward looking, they're likely going to say hey, let's meet in might not even be before the end of the year, it might be in like January or February to say tell me what you have, is that all the expenses you have? Are you sure because we need to file. But if they even if they're only meeting once per year, at the end of the year, and just trying to figure out, okay, we need to shove a little bit more in the qualified account. And maybe you can have any more, you know, maybe you can buy some more capital equipment. That is not, you know, I'm not saying that's well, let me just say this, that is not the accounting, that that someone needs as they're climbing, the echelon of income, if they're still using that CPA, when they're climbing that income bracket, they are going to be paying retail taxes. When everybody else that has reached that level. When they get to a certain level of of success. They figured out how to pay wholesale sales, no different. There's no different there's a retail price, and there's a wholesale price and the people that pay the wholesale price go above and beyond and look for the coupons where the coupons they're in the tax code. Awesome. The IRS is not saying I'm giving out all day. Yeah, they're not putting a flyer out your mail. Grant Wait a minute, are you saying there's no mobile app that they could the tax code mobile app with coupons? I think we should build that. That's a great I should yeah, that's my app. Mark Together Grant. Grant Let's go build that. I bet there's a market for that. Mark Okay. I would bet there is as well. Yeah, absolutely. Grant I love that idea. Okay, so there's something I saw on your profile that intrigued me many things intrigued me and one of those. I just gotta read this off here. Because when I read it,...
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CAIR 71: True Grit To Make A Whole Life
05/20/2022
CAIR 71: True Grit To Make A Whole Life
In this episode, I have the opportunity to speak with someone who demonstrates true grit to make a whole life. Grant Everybody welcome to another episode of Financial investing radios. So today I have with me, someone who is more than what you might think she is an expert on whole life. But do you really know what whole life is? She's going to help us to understand what that means. I'd like to welcome Svetlana. Svetlana Thank you so much. It's such a great joy to be here with you and sharing this space. Thank you for having me. Grant Oh, it's so good to have you here. So I had this opportunity to interview your wonderful husband twice. He's so gracious with his time. He's really skilled in the financial markets. I've even gone through a whole bunch of his courses and applied those. And so it's been I'm a Jeremy Newsome fan. Yeah, yeah. Yeah. And and while I was talking with him, he said, Hey, have you thought about interviewing my wife? And I'm like, Well, what is she talking about? And says, well, she talks about whole life. And I'm thinking well, yeah, whole life such a critical part of life, no doubt. But let's back up set. Svetlana, would you tell us a bit about your origin story where it all started? And how you got into this business? Svetlana Absolutely. Yes. So I'm originally from Kazakhstan. And I moved to America at 19, turning 20 with big American dream as the $100 in my pocket, and I had an opportunity to come and create opportunities and live here. And it wasn't as easy as I thought it was, right. But it is a beauty of a young person that, you know, be 19 and 20. And so courageous, and so naive in so many ways, making those leaves a lot easier than when we become a little bit older. And we have more things that we start considering. Yeah. And so I was blessed that that time, was that mindset, like, what can happen? I'm just going to go and have all of these dreams come true. Grant I'm just gonna go to America, everything's gonna be fine. Right? Svetlana Exactly, exactly. That was like people are so nice there. And so how cool is the wonderful, and it's really a beautiful way to see the world. And I kind of when I was telling my mother, I will come to America. And in five years, I will have all of my dreams realized, I will have, I will get married and I will have a baby and I will have a beautiful home and nice cars and travels. I will have my papers like all of it. I just kind of described for the life that I created. And I knew like just give me five years, it will take me a lifetime in context and to create those things. Wow. But it'll take me only five years in America. And that is the beauty of an opportunity that exists in this country that most people don't recognize. Because when you're born here, you can't think this is how it is. Grant Yeah, you take it, you take it for granted. I mean, I've traveled the planet for 35 years doing business. You do recognize that when you're in other countries, but it is easy to forget it or not be aware of it. Svetlana Absolutely, absolutely. And so when I came here I was like in a Candyland. Like oh my god I can do all these things like it's so amazing. And to start a business you just go on mine create LLC pays $150 get a business license, build a website and you're ready to go. Right like it's a marvelous back home who do you know who do you pay it on the table? Is it my favorite though because the government like I was just like was so impossible, and it couldn't like believe the ease and I recognize truly that there is only one obstacle, truly one obstacle in us. And it is us in our mind, our mindset. Grant The mindset is the obstacle. Svetlana That's a like there is no actually real worldly obstacles that you have to seriously overcome. And yes, you might have a harder life and different things. And not everyone have the same cards dealt. However, you can I was going to library, right, using the computer in the library, did you write emails and just start doing some things. And I was walking for two years didn't have a car. But that still felt like I'm gonna Candyland. And it was amazing because the hardship that I experienced before in my life. Grant So compared to the hardships that you came from, you looked at this hardship of oh, I have to walk somewhere. Oh, I don't have a computer and in your mind, those weren't showstoppers. Those are just things you're gonna go do because you're pursuing that dream, that vision? Svetlana Yes. And the computer is in the library. And it's on the 20 minute walk. Yeah, I mean, my did it was Las Vegas. 120 degrees in the summer. Still possible was a bottle of water. Grant A bottle of water and maybe a hat or an umbrella. Right. Svetlana Exactly, exactly. And so you know, life started. First couple years were very difficult. And then life started to add folding. And indeed, I got married to this incredible man. And we bought our first home. And we have two BMW in the garage. And we I have a great job. And he has an amazing job. We are here pregnant and having a baby boy. And I'm getting my green card in the mail. And I was looking at everything. And it's like four years and eight months. Mike, oh my god, like everything that I told my mom totally can show every single dream. Wow. Yeah. Oh, my how incredible that is. And I was just in the jail and then thinking, Okay, what is next? What is next in my life. And then, two months later, the biggest tragedy of my life happened. Oh, no. And it was the darkest time of the darkest time of my soul that I ever experienced. And I wish no one ever experienced that. But my husband died very unexpectedly, within a week, within a week. Wow. And we had all this plans for the future. And we had tickets bar to go and travel and visit my family and the plants for like, we will come back and get pregnant again. And all of it ended. All of it ended. And I once heard that the hardest thing about heartbreak, and then the hardest thing about deaths is having a funeral to all of your dreams. Right? Because what you saw your life would be is no more. And then it's a time of void. Yeah. And a very deep healing is that in sir in search of what's next. And so during that time, I was very blessed. He was in a new position for the six for six months, and I got life insurance proceeds. Really, and I didn't have to go to work right away. So that money that came into my life allowed me just to lay there and cry, and grieve, and pour into myself, allowed me to get help allow me to do all that I needed and my soul needed and to really rest in grief. And I took nine months off to be with my baby because it was so unfair if he would lose his father to death and then his mother at the same time because she had to go straight to work. shut down everything it just started providing for the home that was created for two incomes, right? Grant Yeah, very difficult. There's some level of an emotional suffering, maybe even an emotion No doubt that you went through as well, I would imagine. Svetlana Absolutely, absolutely. And that was also an awakening into, wow, I need insurance. Because what if I go? What would happen to my baby? Boy? Do I have actually any paperwork? Because I didn't, I had no way or no trust, we didn't have any of that stuff. And I remember when we bought our first home, we received a letter in the mail saying, Would you like to add insurance for 9099? That in case one of you die, the mortgage will be paid off? And my husband was like, ah, should we do it? And I'm like, why would we spend $20 a month? Grant Oh, yeah, at the moment, just now why would we write? Svetlana Yeah, because we never think it will be our story. It's never our story until it's our story, right? It's never our life until it is our life. And that's the unfortunate part about it. And an insurance world we say the money pays for the, for the insurance, your house is what buys it. Like so many people reach out to me when they in a health crisis. And I Hey, can I have a life insurance policy? And the answer is no. Most of the time it is now because now you're not insurable. It is that time where you are well, and everything is going good for you. When you need to just put a month into it, get everything put together will trust Power of Attorney insurance and be done. And hopefully you will never ever ever in your life again, need to look at it. Next 15 years. Grant I mean, the best time to buy insurance was 10 years ago. But if you didn't do it, well then the best times today, right? Svetlana Absolutely. Absolutely. Yes. And so really, that was my coal into insurance runs? Well, because I had to learn about it for myself. And I remember I called my you know, car insurance plays whoever was insured at the time. And they asked me, well, What type do you need? On my there are different types. Like I had no clue. Like, well, I didn't know like, and there was no one really to educate me. And I recognized Well, I'm not the only young woman that is a seeing single widow, with a baby that has all of this questions and insurance world world is huge. You open the door, and there are millions things. Grant So how did you educate yourself on this? What do you do? Svetlana So I got a lot of information here, a little information there. And then insurance agent came into my life. And she told me about certain policy, and I bought it. And then I learned that that policy isn't actually good, that I got it as a policy that I learned that that one wasn't good. And then I was like, Okay, I just need to like figure this thing out. Right. And I was very fortunate that an incredible Insurance Agency, Candace grabbed me, and my G just saw this potential enemy. And so the hunger and the knowledge, so really the heart that was behind it to truly help people. And he sat down with me, and he taught me everything I needed to know and more. And what I find and again, I don't know everything, right? It can be a lifetime on studies. Things are shifting and changing all the time. But I know a lot and a few things that I don't I have incredible people to go to you. Right and and work through those parts, right? And it is usually a bigger project such as estate planning class $30 million. Well, we do what do we do there? Right. So I'll make the phone call my hey, I need you how can we do this together? But pretty much everything else I've done by now and I'm very comfortable with. Grant So what occurs to me, Svetlana, learning about your origin story and how you get going in this is that the common thread and all of this appears to be your grit, how to use the term grit, right meaning you've got this, this desire and this burning desire, right to go pursue something. First, you got to come to America, whatever it takes. And then when you get here, you start ground up and that's just pure grit to make it happen and then then you're thrown this option Typical of your husband passing away. And yes, you needed to heal and do some recovery. But then you got back up on your feet, and you had grit. And you said, I'm gonna go figure this out. And you did both learning, but also trial and error, right? So it was a bit of learning by faith, right? And faith, meaning you would take the next step, you would exercise your faith, try something learn. But each time if there was a setback, you didn't just pull back and say, I'm done. Rather, you would pick yourself back up and keep going again, that's what comes across me is one of your main qualities. Svetlana Yes, it's a beautiful observation. And thank you for saying that. And I would, I would pull back for a little bit and I will, at least in a pass, and that would feel sad for myself and bad for myself. And I would now I'll give myself a day or two, I'm like, Okay, let's be depressed for a day. Yeah. Yeah. Okay. Now it's time to see see beyond, right sees through says it shows. And it is, it has been a lot of personal experience. Absolutely. And then having that greed to rise up again and again. And I think is truly my love for life. I love life and I'm so I find it to be so miraculous, and so magical and so beautiful. Just to have this physical body to experience this life on Earth to experience the depths of love and, and hog and Tai Chi and, you know, be able to eat a delicious cookie. Grant Oh, there you go. Yeah, cookies. I like that a lot. So that leads me to another part of whole life. So when I was talking with your husband, Jeremy, and he said, Hey, do you want to talk with Svetlana? Oh, yeah, sure. What does she do? She does whole life. And I'm thinking whole life insurance, which is, of course, what you do. And then I went to the site, that was I saw off of your email, . And I looked at that, and I'm looking around your site and like, I wait, where's whole life insurance? And then I realized, Oh, this is whole life. Can you talk about that? Because I think this is fascinating. It's two key ways to view Svetlana, she's an expert in whole life insurance, but also in whole life, you talk about that? Svetlana Absolutely. I am a certified life and relationship coach and I work very deeply with the divine energy of, of light, to create healing, healing in mental and emotional, spiritual, on a physical body. And that is what my calling and my life purpose is my life purpose is to free your life people's light, so they can shine bright and impact many truly create a beautiful world. And, and it is as it is whole life, right? It is about mine. It is about heart and energy, and emotions, about your connection with your highest self, your spirit, your faith, God. And it is about the whole wholeness. Because when we only address parts of ourselves in a western society, we're so attached to our minds, right? It's about how smart I am and how much I now. But unfortunately, no, in my view, doesn't create a space of fulfillment, or joy, or just magnificence and life. And my desire for people to experience wholeness, whatever they truly means to them. So they can live out their life purpose, they can share, they live in a world, whether it is through having a financial podcast, right and teach people how to become prosperous. And as my husband says, money don't sell don't solve all the problems, but money solves all the money problems. Right? Grant Yeah, that's right. And money solves the money problems. But not all the problems. I agree. Svetlana Exactly. But it's so mindset can be really be solved. Whereas was finances was those resources when we have them and money is an amplifier. Out of the love that is inside of us. And when we are love, we become so much more love with money and we create healing in a world we go out and build schools, we go out and do beautiful missions, and we just do great things. And the problem becomes when you are dark inside, and then you have all our money, and then you're like, Okay, you know, it becomes more of the darkness, because that's what the inside and managers multiplies what is inside of you. Grant In fact, I remember Jeremy saying something like money just becomes the amplifier, right? of whatever is inside of you. Money just amplifies it. Svetlana Exactly, exactly. And so, Jeremy works on that amplify it on amplifying things, and I work on that to make sure that here is light. Yeah, let's make sure that here is harmony and peace and love. Let's make sure that you have forgiven yourself and those who betrayed you or hurt you. Let's make sure that you learn how to love yourself. Because the reality is I remember having this beautiful 20 year old that I got to work with. And I asked her, please tell me what's good about you? And she said, Oh, Svetlana, I can't. I feel like I am just so selfish and just bragging. But Mike, okay, tell me what's wrong about you? And she gave me the whole list, the whole list of things. And I recognize the madness of this world that we actually been kind of having this applied for? Oh, yes, you are. So you're recognizing how bad you are, and all of these horrible things about you. But when you come in and say, I'm good. I love mine. I am a wonderful, incredible human being. All of a sudden, no one wants to hear it. And everyone is like, oh, yeah, that person is so selfish. And so we go wrong with this mentality that we actually, when we beat ourselves up and talk horribly horrific ly to ourselves, we are fully Grant Yeah, we get held up as oh, gosh, this is good. Sometimes it's viewed as though you're being vulnerable. Right? You're you're you have the courage to expose your weakness, right? Yes. Svetlana And it is very different when you expose your weakness from all the a healed place when you are sharing it, and yes, it is my weakness, and I acknowledge it. But there is nothing wrong with me, I still adore love myself, even though I'm not perfect. And I have this weakness inside of me. Right, and I'm working through it, I'm working on it. And maybe it's a part of my personality. And I want to really embrace that. Also, whether I'm going to heal it and overcome it, or whether I'm going to just embrace it and make it just a part of me instead of fighting with that part of myself, because I'm just exhausted of the sport. Grant When you see people go through this right when they start to embrace whole life and the way we're talking about it here, what's the impact to their lives? What's the outcome of that? Do they end up making better decisions? Are they more kind and loving? I mean, what what's the net effect of of coming to understand that are embracing that? Svetlana They get to start living the life of their dreams. What I help them is to heal so that they can come into the homeless, and then to really look at us, okay, what is placed into my heart by divine for me to live through an experience in this lifetime. And those are your dreams. Our deepest heart desires. Our dreams are not ours. They're not. They are placed by God in our hearts, because this is the way God wants to experience itself in a world. And it is for us to truly be for us to truly experience and to embrace. And the people who work with me, that is really the result they get to live their dream life. Whether they have dreams is to have an amazing partner to have a family to have a business that is prosperous and brings a lot of cash flow and they are creating impact in a world where it is, you know, living at a harmony in a beautiful place because that brings more of the goodness because of who they are, and how they can create, in write, and do podcast and Ted Talks, whatever that is, right. And so one of my primary courses that I teach is limitless creators, the dream scores. My what I take people on this five week journey of creating a dream life, downloading the deepest heart desires. And a lot of times, it is a very first time, they actually true to themselves, they actually admit, this is what I saw truly want. I just been so scared to admit it. I've been so afraid that what if I say that, but it wouldn't come true, or it would come true. But I'm not ready for it yet. I'm not. I'm scared of it. Right. And I held them to really open up, open up and release all the blocks and fears and limiting beliefs and any kind of limitations, so they can live their dream life. Grant And you know, one of the comments you made earlier was that one of the biggest hurdles that you've noticed, coming to America was that the obstacle of mindset. And it sounds like that this approach to what you're doing with Whole Life helps to address that mindset obstacle. Svetlana Absolutely, absolutely. Yes. Because for as long as we have these blocks in our mind, we cannot live the true life, we cannot truly create what is meant for us to create in a world we cannot truly show up in our highest light and be unapologetically. And that mindset is a huge, huge part of it. Grant Huge. It's interesting that you come from this background where you've recognized where mindset is the major obstacle, whereas other...
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CAIR 70: How To Reduce Your Business Cost With AI !!
05/14/2022
CAIR 70: How To Reduce Your Business Cost With AI !!
In this episode, I have the opportunity to speak with Alex Hagerup who is solving the problem of using AI to take costs out of your business. Grant Hey, everybody, welcome to another episode of ClickAI Radio. So today I have someone that I have been admiring by looking at his background, here with me today to talk about some amazing aspects of his journey to solve business problems leveraging technology, specifically AI which is quite cool. Anyway, let me stop right there. And welcome Alex Hager group. Hello, Alex. Alex Hey, Grant. Thanks for having me. It's a pleasure. Grant Thank you. Thanks for being here today and for taking the time. I know you're getting ready to head off trans continental here pretty soon on a trip. So thanks for for jumping on this conversation here today. Alex Absolutely. It's exciting being able to travel again. So I going home to the Motherland for a few weeks is exciting. I haven't been there for more than a few days, for the last three years, actually. So I'm definitely excited. Grant Have have have the COVID situations and those numbers pretty good over there at this point. Alex Yeah, everything is fine. So Norway is completely open again. And it's all good. But But Norway was one of those countries that really looked down hard. And also since the US didn't allow non US residents to actually come back into the country. If you left. It was just a problematic situation to go to Europe in general. Wow. Grant Yeah. What a great opportunity to get home to family. Well, thanks for taking your time here with me today on this. So Vic AI. All right, who is Vic AI? What happened here? How to what are you? What are you solving? What what problem? Are you looking to address with Vic? Ai? Alex Yeah, absolutely. So I'll take a little bit of the background to set that up. So I, I've always been very interested in both accounting, finance and technology. So this is a company that lives in the intersection of those. My mom had her own accounting firm. So I grew up there, which probably influenced my interest for for accounting in general. And I built a couple of companies. But one that I spent three years with just prior to starting, Aki was a cloud ERP system, an accounting and accounting platform that was being used by about 30 40,000 companies back then it's about 80 90,000. Now, and during working there, you know, observe the sort of, let's say, the challenges of accounting and the manual, repetitiveness, the tediousness, all of that from, you know, every day you felt it? Grant Where? I mean, what is the excitement in that? Right? I mean, where's the excitement? Yeah. Did you credit that properly? Alex Oh, gosh, yeah, exactly. So so we were we were just observing this. And then this was back in 2014 15. Just before we started with AI started having a new, you know, like a new summer or a new renaissance in a way and, and we were thinking like this has to be we can maybe like we can solve this in a better way than how the technology has solved it so far. And after some deliberation, we sort of thought that we could create AI algorithms that would be able to actually do accounting transaction processing better than humans. Grant Because that's a really key point I think you're making. So the way that we've been solving this problem up to this point has been, let me take the tasks that we do and just automate the tasks themselves. Right. In other words, let me take your actual transactional activities that you're working through, and just put some increased processing to that. That's how it's historically been done, right? Alex Yep. Correct. And that's been entirely driven by rules, right? So, you know, transaction, Uber, transportation, as, you know, rules based automation, right? And there are all sorts of problems with that. It's obviously better than doing everything manually, right? So we aren't we're progressing through stages there. If you go back before the spreadsheets, you know, everything was done entirely manually. So we are progressing here, but, but what we're building is not next face that comes off there, you know, what everyone is using today, all over the world. And, you know, AI will solve this in a more scalable and gracious way and more more effectively. So that was all right. Yeah. Grant Yeah. So real quick on that, can you articulate how is that different? Right? Because all of us come from this rules based way of thinking. So what is it that AI is going to do better? How will it do it differently than what we're used to? Alex Yeah, I mean, that's a that's a great question. It's kind of the essence as well. So when you when you look at how it happens today, it's not only rules are not only automation, it's automation, and a lot of human hours involved. So you can always ask yourself, why are all those human hours involved? If it's automation, right? So so it begs the question, right, so what happens in reality is that sort of rules and templates and RPA isn't sufficient, because there's so many edge cases, and there's so much variability in the world of accounting. So you know, rules only takes you so far. And then you have to staff up and have human cognitive reasoning step in and do the rest of it. So where AI comes in is that it can do both of those things. So it does the automation without rules, and it can do the reasoning that humans are there to do today. So I always say that AI is, is great at sort of mimicking that reasoning that humans are doing. So one of the areas that we're in is invoice processing. And when I give an invoice to any human, you know, it will always tell me, oh, that's the vendor, you know, that's the invoice number, lots of total costs. But that's not obvious to a computer. And if you're gonna write rules for every variability in the world, you can just end up writing too many rules. So it's just not a, it's not a great technology for it. And AI is way better. So it's just like in the early stages, so that's next sort of digital transformation, transformation journey that we're all. So as Grant So as you know, when you're working in the AI space, and you're saying, Oh, I'm going to apply AI to a particular problem, you end up building different models with different AI characteristics based on the nature of the problem, some more aggression based some more sort of classification based, as your people as your customers look to use your platform, do they get exposed to any of that? Are they even aware of what elements or aspects of AI are at play? Or? Or do they just jump in and start solving the problems they're used to, and then the right sort of AI model behind the scene is executing on their behalf? Alex Yeah, we've hidden all of that from our customers. So we do try to keep sort of Explainable AI in the way where our user interface is explaining why our AI predicted something. But we've kept all of the complexity, so sort of models and model training. And all of that is in the background, we decided to do like an end to end service where the customer, they don't really need to do anything technical. It's, it's, you know, just another SAS subscription that they're using, that they plug into one of their processes. And then we deal with all of the complexity of the models, both global models and AI models, specifically the same for each customer. So we keep all of that complexity hidden. Grant That's awesome. That way, I'm not touching any of that as the end user. So if I see the name Vic AI, I don't need to shy away and say, Oh, wait, I need to be an AI expert. It's more that this is the enabling technology. And it just turns out that you've made that simple for the people without needing to know that Wait a minute. So that brings a question on my use, you know, one of the challenges around AI is the whole notion around bias. And, and, and with the cognizance that's required for humans up to this point, and still largely today to do you know, counting processes. Therefore, that has the opportunity for some bias that comes in right terms of the way things get handled. How do you deal with that then in terms of applying AI so that that bias doesn't creep through? Alex Yeah, it's a great question. And it's a challenge for everything where we're data sets are involved in training, AI. So one of the ways that so one of The one of the good things with accounting data, if you start with that is that it's ultimately numbers and classifications. And you, you kind of want to have that, right? Because otherwise your your books of your business is wrong. So unless you want them to be wrong, you know, you have a very good incentive to keep this right. SO into SO, you know, I think we generally see kind of less less bias in accounting data, and then some other more like subjective data in a way. And then also we draw on data across 1000s and 1000s of customers. So we have customers in both Europe and the US and many other many other regions as well, but the little fewer and most of the concentration in Europe and US. And in all sorts of industries and all sorts of sizes, we have about 13,000 customers on the platform now. So when you start looking at such a wide data set, you also hopefully reduce some of some of that bias. And then you also have auditing processes that sort of sits at the end of their accounting. And hopefully also they'll you know, annually they'll catch corrections, and also fed in as well to make AI. So those are some of the tactics. Basically, it's all about keeping clean data, so that our predictions are accurate. That's really what we're trying to get to. Grant Yeah, boy, that's that's so critical, especially as you pointed out with the with the need to of course, be accurate for the business for sure. All right, so So let's say that you've got this data, you've cleaned it up, you've done the preparation, you're on the Vic AI platform, the question now in my mind becomes, therefore, what changes in the lives of the people that adopt this right and others, they may change? I'm supposing something about the way they do their daily work, or the way the CFO does certain things, or maybe even impact on regulations and audits. I mean, what's the impact of the organization when when this gets adopted? Alex Yeah, I'm also in question. And I want to point out also that the beginning of getting getting live with Vicki AI isn't complex for a customer, because we built an automated system to ingest and clean their historical data, which then goes into our system automatically and train our AI algorithms so that when we go live, we have, you know, pretty good knowledge of what's going to be predicted. We know your system, we know your accounting, we know how you do things. So when you start pushing new transactions through our classification, accuracy is high. And there's no complexity for the customer. In that process, it basically happens automatically in the background. Once you are live with Vic AI, some things will will change. But it doesn't sort of change. Like overnight. One of the things with AI is it gets better and better over time. And one of the things we're driving towards is what we call full autonomy. And full autonomy is you know, the AI's version of automation. But it means that it has perceived this not to need human review. And that's when it's fully autonomous. So that's our sort of end goal with the autonomy of transactions is that, you know, the AI system is perfectly confident in the work that it has been doing. So it doesn't even ask a human to review it. So this this increases over time. So when you start with Aki, you, you have a you know, you have a better interface, you have a smoother operation, you have already probably 50% time reduction in the first month of using the system. Grant Let me stop you on that right there. 50%. So, that would be 50% of those that are doing sort of the daily operational activities, or is that of the CFO? Or who who is that, that that percent impacted? Alex Yeah, that's on the accounting team that is doing the processing. So if you're doing you know, if you have five people or if you have 15 people doing invoice processing, whether they are onshore or offshore, you know, just in the beginning, you can drastically reduce that, and then that percentage just increases over time because you're substituting the AI for for for human FTE. So basically, and and what we see is that everyone wants to do something else than just sit and do like data entry and accounting classification, right? You you, you can be more proactive, you can do more value added work than that. And we're sort of at that phase now where the AI can substitute that's partly augments and also fully run things autonomously. So when you put this in place, in the beginning, there is a little bit of effect right away but you know, you got to read the sign some of your some of your processes and some of your routines because you have a platform here now that is doing Most of the work for you, and you're just reviewing and you're reviewing the AI and training the AI to become more autonomous. So you've got a little on my mind shifts, and some sort of routines, you don't need to double and triple check, check in have four people involved in reviewing, you know, one thing because the AI can tell you how confident it is. And if it is very confident, maybe you can have one person review it in the beginning, and then eventually it will be fully autonomous. If it's less confident, then it will also tell you, and you can review it in more detail. So it's pretty, it's pretty, pretty fascinating. Grant It is dang fascinating. And I'm assuming that there are some that have run into this, and they've worried about their jobs, right? They're like, wait a minute, you're taking my tasks away from me? Do you have to help them overcome that fear and say, hey, you know, you're gonna move towards more value added activities within the organization? Have you run into that problem? Alex So it will we see is that it's, everyone is just squeezed on time, right? Everyone's trying to hit the deadline of the month, the clothes and all of that. So it there is no shortage of work to be done in the accounting piece. And, and just having, you know, having faster turnaround time having more accurate data, because AI is more accurate than humans, like it doesn't fat fingers thinks the same way. And when it's uncertain, it asked for a human verification, a human looks at it, and then you get more accurate than then all the way. So we see that, you know, there's no shortage of things to do. Everyone wants to progress their careers. And I don't really perceive that as an actual problem. But it is like a, you know, people think about that as a problem, but I don't think it is in reality. Grant So this has been several years and coming. When did you start this 2 to 3 years ago? Alex Yeah, early 2017, was 5 years. Grant Okay, that's, that's awesome. And you built this ground up, meaning all of AI development AI technology that your organization's created, right? Alex Yeah, exactly. I mean, it's been challenging. That's why it's taken taken quite a few years, as well as because you we started, you know, completely scratch, and we had to figure everything out. So one of the things that sets the KPI apart a little bit as part of our founding story, where we were able to start the company, we had access to a gigantic data sets of accounting transactions, and all corresponding documents to that. So that helped us just spend the first two years we just spent on data analysis, data science and machine learning development, because we had some thesis and theories that this could work, but we didn't know. So it just had to do that in the beginning, for for a couple of years. So when we saw that this actually has promised, like, we were predicting more and more accurately, and you know, we're gonna get to this inflection point where it's better to use PKI, that do not use PKI. And at that point, people will use it, and then, you know, continue growing more and more customers and more and more data and more and more corrections, and better and better predictions. So we realized we would get to that point. And then, you know, then we raised the seed round back in 2017. And, you know, started developing, Grant What a great journey. I love this story. So tell me about impact outcomes. So you talked about a large number of customers that are using the platform now, what is what's been the results that they've seen? Alex Yeah, so we see. So there's a couple of numbers that we that we statistically enroll from the from the customers, we see that customers have about 80% reduction in the overall time spent on the process. And that comes from two things. One is the percent of fully autonomous. So let's say you're 50%, fully autonomous, that means you spent zero time on 50% of your volume. And then that other part, we've drastically reduced the number of minutes in two seconds. For each transaction a human has to review because the AI has done all the upfront work, humans just reviewing it, rather than sort of processing it from scratch. So you're at seconds rather than minutes. This turns into sort of an 80% reduction in in time. You also have things that we do like prevent duplicate payments, and we have some fraud detection in the system. So you also have some of those benefits that can turn into multimillion dollar when you have a large enough cost base. And then we have audit trails in the system, which helps with figuring out you know, making sure that you know, all of the approvals are doing rights. If anyone has changed in amount or something. It's all logged into the system electronically. So you have some some compliance and auditing benefits from it as well. But right now the main, the main effective impact our customers have, and we typically sell to the mid market and enterprise. So these are larger organizations, they can have hundreds of 1000s, or millions even have sort of vendor bills per, per year, and a substantial amount of people and resources involved in dealing with that problem. So they see very significant ROI from it. Grant So to sell into that particular group, then I'm assuming you've got to have a decent amount of integrations into all of their incumbent systems, right, all of their ERP systems and CRM systems, etc. Right? What does that look like? Alex Yeah, that's, that's true. So we build out these connectors as we as we go, it does, for each connector, the first time we build it, it does take a little bit of time. And then once we have that connect, for instance, you know, to NetSuite or intact or Oracle, the, you know, the next customers that we bring on board, we can leverage the same connector. So it is it is some work initially to build out all of the ones that we need. And then you can grow and scale on top of that for the customer. This is no complexity like we're taking not on completely. So the only thing we need is to know what type of system they have. And we develop that connector as part of the offering. Grant So let's talk about looking to the future in terms of when I'm doing FPA, a financial planning and analysis and I'm, I'm looking at my numbers, and I want to leverage a view into the future. How does something like this help an organization with that? Alex Yeah, that's a, that's a beautiful question. And a big passion of mine, actually. So what we're doing now sets us up to solve that specific problem. So if you think of where we are, now we're in accounting. And what you're talking about is more finance, which is what we'll dive into the idea and the vision that we are getting to is that we want to develop an AI that's basically is a real time cost optimization engine that serves predictions and monitors that in real time, we will be able to help you project kind of what your cost base should be, and how you could reduce...
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CAIR 69: Change Your Life With The Wealth Architect
05/07/2022
CAIR 69: Change Your Life With The Wealth Architect
In this episode of Financial investing radio, I speak with the person that introduced overnight trading to the financial markets. He will give you some guidance on how to build your wealth, I speak with The Wealth Architect. Grant Hey, everybody, welcome to another episode of Financial Investing Radio. Okay, so today I have in the house, it's taken me a couple of tries here actually, literally, to catch Mark Yegee with me here today, longtime expert in the investing world. So grateful that he took the time to come here today and talk with us and share some of his secrets on how to grow your wealth. In fact, I think he's known as The Wealth Architect anyway, without me saying anything else. Mark, welcome. Mark Well, thanks. I'm not I'm not sure I like the title of longtime expert. But you know what, I guess it goes with the territory. But thanks. Great to be here, Grant, and I can't wait to get into what we do and what you do and have some fun with your audience. It should be great. Grant Yeah, thanks again. I appreciate that. So one of the things that caught my eye when your organization reached out and I was reviewing your profile, I just have to start here. There's this tip here about you getting into this world into the investing world at the age of 12. I mean, holy smokes at the age of 12. I was milking cows and hauling hay. I mean, there was not a stock market in sight. So I asked you, I mean, the only stock I saw had horns, right. And where I was milking it. So you know, if you'd have said, How's the stock market? We're like, well, we got, you know, 50 cows in the pasture, but like, What are you talking about? So, how did you get into this at 12? Mark Well, you know, my dad was a grew up on a farm. I didn't, I grew up in the city. And so I you know, I mowed my yard and cleaned my pool and got paid to do that. And every day, I would see my dad reading the Wall Street Journal, and it had all these symbols in it with numbers by them, and he would circle stuff. And I was so curious about what he's doing. And finally, one day, I'm like, Dad, what are you doing? I think it's like you thought I was ready. And so he said, Oh, this is how you invest in other people's businesses. And I was like, Oh, great. So over time, he started to kind of teach me that, you know, you're running your own business, doing your lawns, but you can also go out and invest in other people's businesses. And I thought that was fascinating. And after a while, after maybe a couple of months of telling me about it, he goes, but the only way you're gonna learn it is to take some of your money and put it in and I did. And so my first stock, I think it was 12 or 13 years old. It was right around that time. It was it was 100 shares of a company called Ailey company. Grant I've never heard of, I haven't heard of them. Mark No, I don't think they're around anymore. But they were they was this women's clothing store in the malls. And it fit all the criteria. Low P I mean, my dad taught me a few things. And it was alphabetical that I went, you know, I finally went, Hey, here's one. So I circled it. And I bought, you know, $300 worth of that stock was 100 shares at three bucks. And I just would watch it every day. And I was fascinating. Oh, there's the new print on it. And there's a new price. And the stock went to $6. So it's it was probably the worst thing that could ever happen. It's like, it's like when you grab the golf club and you hit it right down the middle. You think you're a good golfer? This is easy, right? It's as easy as like this, you know, or if you go to play craps and you hit it on the first you know, first dice roll. And so I I invested again, I saw commercial on TV, you know, and it said us, it said Allegheny Airlines is becoming US Airways or us there. I think it was at the time. Yeah. And I was like, Wow, what a cool name for an airline. And I you know, that was the only reason yeah, I think it might have might have met some of the other criteria as well. So I bought it and it went from 17 I remember to 35 so I doubled it again, which is probably the the next worst thing that could have happened but now I'm like, this is a piece of cake plus I don't even have to work the money is doubling and yeah, anyway, so you know, I guess I could buy more candy than I could. But that was it. That was the beginning and then he started intermediate. introducing me to books. My dad was a big Personal Growth Guy. So I had read, I had read books, you know, by Dale Carnegie very early on, I read books by Edward Thorpe McShane, the business who wrote a book called, oddly enough, he wrote, this first book was called beat the dealer need to deal with a guy who was an MIT professor. So he taught math at MIT. And he went to Las Vegas, and he figured out how to beat the roulette tables. And they, you know, he had another guy helping him and this was kind of a rudimentary metric computer in the 50s. And he figured out where the ball was coming out, and how quickly it was anyway, he figured out a way to get the probabilities in your favor, and he started to beat the roulette tables, and they kicked him out of Las Vegas. So he went back, and then he figured out well, I'm going to figure it out on Blackjack, and you've heard the story, there's been a movie made about him. Is that the movie? 21? Yeah, yep. All these kids went to MIT, you know, the students. And he brought them they all cleaned Vegas out and then finally got kicked out of that. And then he turned his his efforts to the market. And then he wrote a book called beat the market. And it was basically how to buy a stock and sell the warrants against the stock, which today are basically known as options. They're still warrants, but most people don't know what they are. And it was covered. It was a system of covered calls before they even had options. They didn't have options until 1971 or 1974, I think. And so but I was fascinated by because my dad was like, Oh, you got to learn this. And it was this thick book. It was really boring. And but I, I started to apply it. And I applied it so much that when I was 16 1718 years old, by the way, I bought my car with the winnings and the monies that I made in that those first few investments. I set up a brokerage firm at EF Hutton and my dad had this old timer broker. And I said okay, Harry, I want to buy 100 shares of IBM and I want to sell the you know, the call options against it. And he's like what? So we had to call in New York and get the options principal from EF Hutton on. And he understood why zoom, but my broker didn't even understand I did teach him what I was doing. And so all through high school and college... Grant And this was a high school you did that you sold your first in high school high on IBM? Mark Yeah. So IBM, and this is back when you pay a commission of $300 to do IBM. And they had quarterly options. And you know, the different it was a different game. And now we have so many more tools that are at our disposal. That's great. So yeah, I did this all the way through college. And finally, you know, I had several different entrepreneurial ventures and then I actually sold copiers, which for me was the worst thing. Anybody. Grant Like they just sort of jumped into the white when you're selling options, and you went from that to copiers. What happened? Mark? Mark Well, I mean, when I went to college, I didn't think that making money in the stock market was going to be on my my career. So I went to college. I got a marketing and business degree, and everything was hunky dory. And then I got out and pretty. I I started an entrepreneurial company in college. I was back when the Swatch watches were this big craze. Oh, yeah. And you remember those people put 10 Swatch watches on their wrists? Yeah. And I thought, Well, I went to the University of Florida and I thought why isn't there a swatch watch with a gator on it? Like a University of Florida Gator, you know? And, and I went to the I went to the, you know, the alumni office and I said, Can I license the gator. And this was back before the internet. This was back really? Right around the time faxes were becoming popular, but still pretty early back in. In 1980. What was this 85? Yeah. And they licensed the Florida Gator trademark to me. And I figured out a way to get to Hong Kong. I had no money at all. And when I was a junior and senior in college, I went to Hong Kong and I met manufacturers and I figured out a way for them to put the gator on these watches that I wear orange and blue the color the exact colors of the school. Yeah, and I brought back these you know, 2000 watches are added, manufactured and shipped. And I had them in my college wasn't my dorm room was my fraternity. I lived in the fraternity house last semester. And so I had them stacked floor to ceiling all these watches, right? So I go to the games, and I would sell these things and and I learned a lot about a lot, right? Traveling, manufacturing business, you know, buying good quality products versus crappy products. And I expanded to 23 schools in the southeast and finally just got out of that business about four years later. And then I sold copiers after that. And I that was miserable. But it was that was again instructive. And then finally I I said why I've been doing the market all these years. Why don't I just go do that? Amazing. Yeah, I got a couple of I got a job with a guy named Ernie Ollie who had already discount old discount stockbrokers. It was a discount broker like, like Charles Schwab, they were actually good buddies and they started when those got deregulated in the 70s. And I worked for Ernie for or a year and a half, two years, something like that started my own brokerage firm with a partner. And then we grew that to a to a pretty big venture became a Wall Street company that applied to do this financial technology, I could bore the I could bore you with all the little stuff that I've done in between. But it all has led me to this spot where I had a, you know, a big trading firm, Wall Street trading firm. And we traded, you know, billions of dollars worth of securities. Grant I saw that, that's well, and did I read it right? That did you guys introduce after hours trading? Is that true? Mark Yeah, that was actually my idea. And everybody thought I was crazy at the time. But I thought, you know, we have this system that all we do is if somebody wants to buy and somebody wants to sell, our system was a computerized system, they just matched those sellers. And I said, why does that have to stop at four o'clock? Why Can't We? If somebody still wants to put the order on? What can we do it a 401? And then if we can do it a 401. Why can't we do it at 601? And then why even shut the thing off? Let's just let it run all night. It happened automatically anyway. And so yeah, we introduced after hours trading in 1999, I believe. And I was on NBC Nightly News with Tom Brokaw. And you know, a few things. Grant And then, and you're now you're talking to me now how am I now? Mark And now I've moved up to talking to you. Yeah. Grant Wow, you finally got up to Grant Larsen. I mean, Tom Brokaw, it's been a long time coming! Mark So just a stepping stone. You know, you got to stand on the giants that came before you gotta get to the grant Larsen. So. But, uh, but I'm glad to be talking to you. Because you know, everything that I've done in my life has led me to this exact point. And that exact point is now where I have a few hedge funds that I run. They're all based on all these mentors and all of them knowledge that I learned over the last 45 years. And now we help people call, you know, make what we call Safe, reliable income. Although if you look at it today, with this market, it's not safe, reliable income today. Grant Yeah, I turn my head and I'm looking at it that can you say sell off? Mark Yeah, don't don't even look. It is a light volume sell off. So I believe that there's a bounce coming in a couple of days. But boy, it's, it's painful for a lot of people right now. It's, you know, people think you just buy a stock and you hold it. And that's the way you invest. And then you get these 25% corrections in the market. And people's 401 k's are decimated, they go to 5060 70%. Yeah, it's just a shame. It's just a shame. Grant Ever since November, I saw got it at the end of last November on my systems and went, Okay, I'm gonna start preparing to hedge here. So I've just been building my hedging positions since then. And yeah, we've had some interesting volatility a couple times. But right now it's down hard for sure. Mark So it's horrible. Yeah. And you if you started in November, you probably if you correlate it, it's the exact day that Jerome Powell from the Fed said, we're going to start to raise rates. And from that point, we're down about 27 28%. And some stocks. I can tell you some stocks are down 50%, 60%, 70%. Grant Yeah. Facebook and others. I mean, they're down like massive 5060 out, yeah, Netflix got hammered with your training thing. And, yeah, just a lot of them are down really soon. Mark But it doesn't have to be that way. Right. Like, you know, a lot of people just don't know what they don't know. And we tell people that they can make two to 4% a week. Now, that doesn't always happen. But our goal is just like that analogy that I threw out before about the craps table. It's, it's to get the odds on your side, right? Yeah, I mean, I know, it's this is not gambling. But if you use gambling as an analogy, you can understand it better. If you're sitting around a poker table like Annie Duke or Phil Ivey or those guys that are on, you know, the the World Series of Poker, they don't win every hand. But if you have a pair of aces, you have the odds in your favor. If you stay in, unfortunately, sometimes three kings comes up and your opponent has a king, and then you lose, but that doesn't mean you shouldn't have been in the game. So what we try to do is we try to create safe, reliable income by renting stocks, to other people that are going to our B that are willing to gamble and pay us a premium for having the option to buy our stock. I can explain that a bit more with an analogy, if you if you want to hear it, but that's really what we do. Grant And I'm selling options, then that's that's your main strategy. Mark Yeah, yeah, we buy we buy a good solid stock. So we have, we have a system called the cash flow machine, right? We call it the cash flow machine because you you put cash in, and then it gives you cash out more cash. And that's it's, it's a system that creates income, using what we call the four cornerstones it's the right stock, not just any stock, the right market, because you want the tailwind to be behind you. So we use a component of market timing and does help and then it's got to be the right spot on the chart. And usually you can find a high probability spot on the chart where this were the end institutions are behind the stock exchange in the right direction. Yeah, and we don't want to be against the institutions. That's the big money, right? We're little people. Yeah. So we want to be with them. And we can see where they are, they leave footprints on the chart. And then we go in that direction. And then the fourth Cornerstone is we squeeze the juice or we collect the rent. And that's the option premium that we get for selling upgrades and income. And it's a defensive strategy that we make, you know, two to 4% a month, conservatively. Grant Now, there's, you know, there's obviously a fair amount of margin that's needed in order to do this kind of thing. So you typically need to have fairly decent size accounts to do some of that stuff. What what's sort of the entry level that you see most of the people come in at how much is what sort of account size or capital do they need to have? Mark Well, it depends, we have a breadth of options that you can use so so I have a hedge fund that I run using this strategy for accredited investors, people that are worth, you know, more than a million dollars, you know, rich guys, basically, but not everybody qualifies for that. And I want to do whatever I want to make this accessible to everyone. So we have a set of courses. And we have my favorite thing is a mastermind group. And so the mastermind group is around a series of courses, and their video courses over my shoulder, I show you how to do the trading and you and you understand the philosophy behind it. And I give you the whole strategy. And then it's also surrounded by a full ecosystem of support. So we have like minded people that are also giving you support people that have just gone through the learning that you've gone through, you get mentorship from me, and I've got, you know, for decades of doing similar things in this, you get, you'll actually get something called the private access group where I put out the actual trades I do in my hedge fund. So you can learn from them, mimic them, do them, you know, do subsets of them, whatever. And then on Friday, and again, this was what I was alluding to a bit ago, on Friday, we have a mastermind call where we all get on a zoom call, some of us will share our screen show the trades we're making, I'll usually teach a concept about the current market or something, you know, that we should know. And then we hold each other accountable through a chat group all week, like, Hey, what are you doing? Who's doing what during the Fed announcement? Why are we you know, selling, you know, the Tesla when Tesla's coming out with numbers, you know, things like that. So to answer your question, that mastermind group, it's an investment in yourself, I give a money back guarantee, if you don't make enough money to cover the tuition because it's not a it's not a small amount. But it is the small amount of it's an investment in yourself, and you make it back with your investments. But in order to, for me to feel good justifying that you need about $150,000 to 2 million as a minimum, Now, not everybody has that. And I've had people that just you know, take the courses and do extremely well with five or 10 or 15,000. But they're not going to afford to be in the mentorship program, and the mastermind group and all that kind of stuff. But they can take the courses. And so we have a full breadth of offerings for people just so that we can they can learn it. I also have a free course on my on my website that you can sign up to take that kind of introduces you to the concept of what we do. You know, we got all kinds of stuff. My goal is Grant, it's financial education, right? We don't teach people about money in school. We just don't Yeah, it's it's not at all. I don't know about you, but I use money every day. I don't use Romeo and Juliet every day. And I don't use the Pythagorean Theorem every day. Grant One I don't use while shopping the grocery store. Okay. Mark I haven't used the Pythagorean Theorem, I don't know in at least a week. Yeah. And, you know, I don't learn I don't know much about you know, I don't use Cleopatra, and Henry the Eighth and his wives every day, but boy, I use money, it would be nice to know, would have been nice to know without having to go outside and learn how to buy houses in real estate, how to invest in the stock market, how to do my taxes would have been nice to have learned a little something like that. Yeah. So I believe that that's the biggest thing that people can do is they can invest in themselves by getting financially educated. And so that's part of that's a little part of what I do in the world is is help people with that. Grant So it's interesting that you're making this available to a wide range of people regardless of where they are right certainly you've got the capabilities to help those that are accredited, but for the person that's just trying to get going I mean, you walked that journey so you understand that and therefore...
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CAIR 68: Real Estate Returns Without Being An Expert !!
05/04/2022
CAIR 68: Real Estate Returns Without Being An Expert !!
Hey everybody. In this episode, I have a fascinating conversation with Heather Dreves who shares some secrets on how to get returns from your real estate without being an expert. Grant Everybody, this is Grant, Welcome to another episode of Financial Investing Radio in the house with me today is Heather Dreves of . Now someone reached out to me and said, Hey, have you taken a look at Heather's profile. And when I reviewed it, I started to realize, hey, there's some things that she's talking about that I've been able to dip my toe in, in the real estate space. And when I saw what she was doing, I thought, oh gosh, this would be really fun for us to hear more about the unique solution that they're bringing to clients. So let me take a breath and say welcome, Heather. Heather Well, thank you for having me. I'm excited to be here. Grant Very good to have you here. And you know, when we were talking before we got started, I think you probably live in one of the most beautiful places on the planet, which is awesome. So thanks for coming out of the cocoon of beauty where you guys live, talking with the rest of us. Okay, so first things first. Tell me a little bit about how your dreams and what got you going into this business area in real estate? Heather Yeah, well, I think everybody has a story, right? Like, a lot of us started with something else. And then was led down a path that was probably a better calling, per se. I went to college to be a teacher and decided I really liked my children but wasn't really interested in spending all day with everybody else's kids. That's it. Grant That's good to find out. Heather Yeah, yeah. Well, my kids gonna test it out. They're like, You were terrible at helping us with homework. But anyway, so stayed home with our kids for a long time, we were kind of entrepreneurs and my husband was running an indoor soccer center facility. But I had a very good friend of mine that was in the private money industry. So when our youngest son was in school full time, I decided to go back out into the adult world. And he's like, you know, come to work for me. I said, I have no idea what you do I have a mortgage, is it the same thing? He's like, No, come down to my office. So long story short, 20 years ago, walked in there and just, it blew my mind. I had no idea that one, if you were a real estate investor, you could get funding outside of a bank and traditional sources. And two, I had no idea that you could invest money that way. I thought everybody went to a financial advisor, everybody, you know, stocks, bonds, mutual funds, like I just I was, my eyes were wide open. Grant I mean, that's such an uncommon knowledge just right there. Even some of our listeners will be like, wait a minute backup, say that phrase again, you can do what say that one more time. Heather So you can buy real estate, and get funding for real estate transactions outside of a bank. So you can acquire what we would call private money lending to buy real estate, a lot less restrictive than a bank, you know, they typically private lenders will look at what we call an after repair value, which banks don't do, you know, they want to know what's that property worth as it sits, and that's the most they're gonna lend on it. private lenders are much more creative. And they can look at a property and say, hey, I can see the value you're going to add, and I can see your vision. Absolutely will end on that. And so, that was mind blowing to me first. And then I started started with working with investors that said, you know, I've got money in the stock market, but I also want to invest in real estate. But here's the deal. I don't want to own the real estate. I don't want to rehab the house. I don't want to deal with a tenant and toilet but I want to reap the benefits of that. Grant So intended for more passive participation. Is that the idea? Heather Absolutely. Yep. So I'll huge majority of my clients, you know, have been active real estate investors in the past. They like real estate as an asset class. Again, they don't want to do it themselves, but they want To be the lender per se, and so there was this opportunity to match active real estate investors with people that are looking for a more passive Path to Wealth and and match the two and it benefits everybody. Right? Grant So what's the what's the typical profile of someone coming to service like this? Heather I would say on the borrower's the active investor side, you know, there there are people fixing and flipping, and they're everything from the guy that has a full time job that's doing it on the weekend to the very active clients that are for like 100 houses, really now they don't want to deal with a bank. There's too many restrictions. You know, we obviously have a very clearly defined guideline process and underwriting process, but it's much different than a thing. We're we're focusing on the asset, and then also focusing our attention on the borrower, we're making sure that they have the financial wherewithal to actually finish the deal. Can they make the payments, you know, all those things, we look at credit. But then on the on the passive side, the clients I mostly deal with there, you know, one of the niches I've really gotten involved with is high net worth dentist right now. Grant Did you say dentists? Heather Dentists. Grant Okay, I did not expect you to say dentists. Heather Well, here's the thing. They have tons of capital, right? Yeah, they have no time to manage their money invested, you know, and a lot of times their biggest asset is their business, they'll sell their practice, when they retire. Now, they have this influx of massive capital. Oh, interesting. A lot of them are very educated with real estate, but they don't have the time to do it. And so I would say that the profile for my passive people are people that have started to create some wealth for themselves, and they want to either create cash flow, so maybe they're retiring. And they don't want to tap into what they've saved, but they want to live off their earnings. Got it, or a new niche I've really I'm pretty excited about is our growth minded clients. So you know, I don't know how much you know, about a real estate fund. But for a long time, you had to be a high net worth accredited investor to even ever think of investing in these types of funds that we're talking about REITs. Yeah, well, we are similar to a REIT. But we are a privately managed real estate. Oh, interesting. Okay, got it. Well, we're privately managed, but the model is the same. It's real estate assets, throwing off profit. And that's how people make money as off their earnings. But 10 years ago, you could only open that type of fund up, if you were what's called an accredited investor. That's the only people that could invest. So you had to have a million dollars in assets over income of $200,000 a year 300. As a couple. We feel really passionate, we think everybody should have the opportunity create wealth. So four years ago, we actually have the ability to open up what's called a Regulation A fund, and anybody can invest in it. We started our minimum at $1,000. And it's open to anybody, and we pride ourselves on this, it took a long time to get approved for this spot. Grant That's fascinating. Okay, that's the first I've heard of something like that. How many organizations do that? Heather I mean, I haven't heard of anyone, not many that are a real estate fund. Most of the time, they're a crowdfunding platform. So you're, you know, you're investing in a platform, that's an angel investor, or they, they provide business loans. There are only a few real estate funds in the United States that were approved for that. So it's pretty uncommon. Grant That is, wow, that's very interesting. Okay, that must have taken a lot of effort to get that I mean, so that's feels like that's such an untapped market too. Huge market. Heather What we cater to is we work with a lot of clients that have 401k Is that they didn't move from a previous employer have small Ira balances, you know, they funded it with six grand and, and then they never did anything with it. This is a great opportunity for those kinds of funds. You can roll those accounts over to self directed custodians. So they're still tax deferred, you're not, you're not taking a distribution on it, okay? You're just, you're just now deciding where you want to invest it instead of having a financial advisor or a money manager, and I'm not here to tell you to people to pull all their money out from their financial advisor, really, it's just a way to diversify. And it gives people the ability with small dollars to invest in real estate because a lot of people think, well, I've got to have, you know, a couple 100 grand to buy real estate, no, you don't, you could invest in a fund that's investing in real estate and you reap the benefits of it and you have zero headaches. Grant That's, that's awesome. So let me say back to you because it sounds almost too good to be true. Okay. You're telling me that someone could take their four When k or whatever other capital they have, there's not a bar, a minimum bar, they can roll that into this investment fund investment fund is going to be making the investment decisions, as well as managing the properties. And these people then just participate that investment participate in sort of a passive, passive return is that you said? Heather Yep, yep. Grant That's really awesome. Heather Average yields are eight to 9%. We've managed funds for 10 years. So we have a really good track record. They are very regulated by the SEC. So there is a another set of eyes overseeing it. And they're fully audited funds. Grant Okay. Okay. Then what's the risk side? Heather Well, the risk side is, you know, not any different than any other investment, right risk is the market shift values decrease, I will tell you that our funds are a little bit different than most in the sense that we focus around residential real estate, okay. And we were not what people would call a syndication where we're investing in apartment complexes, we focus our investments around single family up to four units, all in the affordable housing market space. So we do two things with the funds. So part of the fund, we lend the money out. So real estate investors that are wanting to fix and flip we'll lend them money, we take a first lien against their property. So worst case scenario, they don't pay, we foreclose on the house. And now we own a house with 30% equity in it because we don't lend more than 70% of the the other portion of the fund we buy real estate, specifically in Coeur d'Alene, Idaho, and Spokane, Washington. So we invest in projects locally. We don't preach people trying to manage a rehab five states over and we don't do it either. So that's our model. Grant So are all of your properties in that area, then? Heather Yes, all the hard assets that we buy are only local, we went out is nationwide. Grant Because I've worked with I've worked with some groups that will take the approach of the look for places in the US where the volatility of the real estate market is small. The intent is to create a cash flow through sort of this renter model, if you get appreciation on the property great, but it's not about that it's more about sort of that rental cashflow. How different are you from from something like that? Heather Well, we look at all of that. And that's another reason that we stay in the affordable housing market space. Because let's let's say that, you know, our exit is to rehab a house and flip it and the profits flow back into the fund and the market shifts. When you're in that affordable housing market space, you have a huge opportunity to cash flow that property in the event that you need to write out, you know, values decreasing. So we're much like that. And I think you'll have to be as a fund manager, you have to be nimble, you have to have multiple strategies. If you start relying on one stream of income for that fund, you're in big trouble when things change. And so we're much like that I you know, in the past, we've done very well, fixing and flipping, and our clients have done very well fixing and flipping, we're right now educating our clients that hey, some markets are turning like in an inflationary time, real estate's a great place to be. But it's also a great place to be for rental market. And so we're seeing a ton of opportunity for cash flowing properties. And so we're starting to add that to our to our portfolio. Grant So a couple minutes ago, you were talking about another class of investor that sort of a high growth or high high growth minded and then I think I may have entered interrupted you on that. What is it about them that you find interesting? Heather Well, the nice thing about our funds is when people make a decision to deploy capital through our funds, they can set their accounts up however they want. So what I mean by that is, they can either set their accounts up to reinvest their earnings. So earnings are paid out monthly. So we pay out all profit, which is really different than most real estate funds. Because if you're investing in a fund that's buying an apartment complex, for example, typically your returns are realized five years down the road, you get the benefit of depreciation, which is great, but you don't typically see your high yields till they sell that property. Right, right. Are our funds cash flowing? So we're lending on loans or paying off or buying properties? We're selling them. So all those earnings or profit are paid out every month? So you can either reinvest your earnings and roll them back into your equity membership, which is yeah, if you're working with self directed IRAs, that is an awesome option because you don't have these dollars going back. All right, and then they sit there and deploy until you have enough so you can reinvest for more growth minded clients, or for my guys that are looking for cash flow, you know, retired sold their practice trying to replace their income. They liked the monthly model because they're getting, you know, the earnings. Yeah. Grant So on the property, so sorry, Heather, quick question on the property itself when it's purchased, is it the fund that is on the property that owns the property? Or is it you know, allocated to the individual? Heather No, the fund owns the prop. Yep. Any loans that we originate? The fund is the lien holder. And that that's another thing is these are tangible assets. So risk is, at the end of the day, the markets go haywire, we just start liquidating assets and paying people off would be worst case. Right? Grant And that's how that's very interesting. Because, you know, I, currently, my wife and I, we invest in properties, but we do it where we're the first in other words, it's, it's, it's on us, right? So we have property managers that certainly take care of it, because we really like that, you know, cash flow kind of idea, right? And you want to be sort of passive with it, for sure. But at the end of the day, it's it's my name on it, right. And I think that's a unique thing about what you're describing there. I'm listening to a gun, though, that would distribute the risk, right, and spread it around there a little bit as as the individual investor. Heather Very cool, right. And that's what you know, a lot of people like, I have a large percentage of my clients have done real estate in the past, they've owned rentals they've owned, they've funded notes, they've fixed and flip, they, you know, developed and they're kind of at the point where they've, they've got capital now, and they don't want they want to retire. They, they want to, they want to golf, and they, they don't want to hear from a tenant that their toilets plugged in the middle of the night, you know, even though you're using a property manager at the end of the day, it's still you paying for it. That's right. That's right. You know, that's where I think there's benefit there. And then also for our clients that have smaller dollars that, you know, our husband and wife both working full time with kids, they don't have time to be rehabbing a house, this is a way that they can start to put that money to work for them. And it's shocking how quick it grows, especially your tax deferred accounts, self directed IRAs, and self directed 401. K's are like, people don't talk about it enough. It's, you know, you can do traditional, you can do Roth, if you're not working currently, for the employer that provided the 401, you can roll that over and start deploying that capital. So there's just so many other options out there that I just don't think people are aware of. Grant What's your take on potential impact to this model with, you know, interest rates slowly nicking up there from the feds and such any any concerns there? Heather We do. We talk about it. We meet multiple times a week, there's three fund managers to include myself, I think what we're already seeing, I mean, our market is a little different. It's still very hot, but we're starting to see it take longer for houses to sell. I think prices are going to stabilize. I don't know that we're going to see a I don't think we're going to see a downturn like 2008. I don't think that's going to happen. banks aren't lending at 120% of value. But at some point, I would I think homeownership is going to be affected and there's going to be a huge opportunity in the rental market. Grant I think it'd be a soft landing, right? Heather Yeah, yeah. Well, there has to be right. Yeah. You you can't have interest rates as low as they were in values increasing at the pace that they were. Grant No, it's crazy, right. Especially what the last. I think you're saying before we started chatting wasn't like you've seen it just in the market year and 40% valuation increase just in the last two years. Is that right? Heather Yep. Grant Yeah, boy, that's in the Wall Street. Yeah, that's better than this. Heather We bought a little house close to my office down here. My our younger son was going to call it there's actually a small junior college here. And three and a half years ago, we bought it for 200. And I was sweating bullets. I thought, oh my god, we're just overpaying for this house. The house next to it just sold for 450. I was like, Why didn't we buy like five of five of these? Yeah, I was thinking but you know, it's but but again, that shows you that a lot of locals in this market are selling because it's a huge opportunity, right? They'll never make as much money but now they're displaced. And that's why as a as a fund management team, we're saying hey, multifamily, small multifamily. We have several duplex projects going and for plexes because people have to have somewhere to live and at the prices that have increased here, you know, most of the locals can't afford it. And so they're going to be you know, looking for housing. So we think that that the housing market right now, is it the opportunities in rentals? Grant Yeah, that makes sense. Quick question about your clients in terms of preparing them. So given that some of these models are new to a certain group of people, what do you guys do in terms of getting people up to speed or educating them? Is that some of the things that your organization does? Heather Yeah. So the interesting thing about our company is we actually are an education company. First and foremost, we put on so it's interesting, we used to put on live events, like maybe at most for a month, usually two to three will COVID hit. And as everybody else in the education space that did live events, quickly, you're either closing down or you're pivoting saying how do we still pull this off? So what's really cool about that is we went live with all these these events, webinars, podcasts, online live events, and now we put on...
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CAIR 67: How To Add Crypto To Your Portfolio
04/28/2022
CAIR 67: How To Add Crypto To Your Portfolio
Hey everybody, welcome to another episode of Financial Investing Radio. So in this episode, I have the opportunity for a second interview with Jerremy Newsome. What's interesting about this with Jerremy is he's got this organization called Real Life Trading. And he's got this. I love his mantra. It's basically they're there to enrich lives, and he gives away tons of free financial investing and trading courses, just gives it away. He feels like like this should be available to everybody. And he told me and it wasn't part of the interview afterwards, we were talking about it. He told me about an upcoming deal he's got I think it's on May 5th. If you go to . What he's doing is he's given you an opportunity to get $200,000 to invest, you got to prove yourself, you got to follow some rules, otherwise, they'll they'll fund your account. Kind of an interesting, interesting deal there. Today, though, in this conversation, Jerremy and I are talking about crypto trading, adding it to your portfolio. Everybody welcome to another episode of Financial investing radio. So I went and got on my knees and begged and pleaded to one more time to get in the house. Mr. Jerremy Newsome first of all, thank you, Jerremy, for taking the time to be here. Jerremy Man, my pleasure. You're so welcome. And I'm honored. This is my privilege as well. So thank you for having me. Grant So you and I spoke, I don't know, few weeks ago, and since we spoke, I went and I checked more of his stuff out, you guys get to check his stuff out. I want I checked out his stuff. And I went on to his site real life trading.com. And, and he's got all this free content out there. It's incredible. I've spent 1000s and 1000s of dollars for that kind of training before I was amazed you had that out there. And I've knocked out your first three courses on it. And I have to tell you, first of all, you're an awesome educator. And second of all, you really know the markets and you teach them well. And third, I've been applying as techniques and it's made a direct impact on my on my trading activity. So okay, there you go. That's my hero worship. Jerremy Thanks, dude. It means a lot to me that you did that because you're a man of your word. You said you're going to and you did it. Yeah, that's phenomenal. Grant Yep, sure did. Sure did. Okay. So what happened then is after Jerremy and I talked last time, I said, Gosh, that went really well. Are there other topics that you cover? And we're texting back and forth? He's like crypto and like, serious. Okay, of course, that's before I gone through your training courses. Now. I realize oh, yeah, you definitely are gonna, you know, knock it out of the park and crypto. So we wanted to discuss crypto in this world that has so much controversy around it. Some are like all in on it something it's you know, the devil's mother. It's just got all sorts of different views on it. But bottom line, let's start with what's attracting people to crypto. What are your thoughts there? Jerremy You know, that's a good question. And I think what attracts most people, and this is probably a slightly unfortunate answer, but that's okay. It's just like explosive games. I think that's what attracts people to it, because they're like, well, this thing is brand new. They heard about Bitcoin, they probably saw it somewhere around five to $10,000. Back in 2017. It's all up to 20,000. And now it's at 34,000. And so they're just there, they're doing the math right. People are like wow, there's a lot of opportunity. There's a lot of returns to be made. And same thing with NF T's are same thing with just active crypto trading like there are ridiculous ridiculous numbers and some huge success stories that have happened in crypto for sure. Grant Yeah, absolutely. So when you think about how much money I have to have in order to trade you know, options or or to be buying stocks or Doing futures, they each have their own requirements. What does it mean for crypto? If you want to get into that world? What do you need to have in your bank? Jerremy So that's what's cool, I think probably later down the line, but certainly, an aspect that will attract people is you can start with any amount of money, there's no regulation on how much money you have to have. So for example, as you mentioned, you have to have $25,000, the day trade, right at least, if it's if it's in a margin account, and if you're here in the US, but you have to have a certain amount of money to place a certain amount of trades in a certain period of time. Well, with crypto, you don't any amount of money, what 100 bucks doesn't matter. And what's incredible about that is you do have the opportunity, in my opinion to then offer new insights to new individuals, right? Maybe their children, young adults, maybe their 1415. Kids can trade this stuff, right? You can give, you can create your own account, put three 400 bucks in there and let a child go wild and see how they can trade because there is no if you don't use margin, which is pretty hard to do actually in crypto. So if you don't over leverage yourself, which again, is very difficult to do, the chances of you losing all of your investment are pretty small. And the chances of you losing more than you invested. If you don't use margins are pretty much zero, at least to my knowledge. I haven't heard anyone doing that yet. Therefore, it allows really an experienced individuals to get experience through the through the school of hard knocks, you know, why not? But with any amount of money, man, that's incredible. Grant In fact, on that point, just real quick. So when when we talk crypto, what are the what are the main instruments that you're referring to? Jerremy Man instruments I would say like the the decentralized, peer to peer currency that most people will probably heard about Bitcoin, you have a theory of them. There's a very popular website called coin market cap.com, coin market cap.com. And any individual can go there's free and they can kind of scroll through and determine and visually identify what are some of the larger coins, tokens projects? What are people doing? And how are they doing it. And it allows them to really just see what's out there because from a market capitalization standpoint, it's a market capitalization, meaning how big is this asset, I usually stay in the top 30. So if I'm trading something, if I'm putting my own currency into it, my bitcoin or US dollars, whatever, if I'm buying a token or a project, I'm usually staying in the top 30. So that I can assure myself of liquidity, which means the ability to sell, right, so there's almost always a buyer on the other side of the screen. Grant In fact, I got involved real early on some of the Bitcoin stuff, but there wasn't as much liquidity back then. And that turned out to be good and bad, right? Those those a lot of that's overcome, certainly, obviously in the Bitcoin area. But that's great advice to stay on the top end of those is I've come to get to know you and your mission, which is to enrich lives, right? I love that about your mission. In the fact that you're you're taking Kryptos away to teach younger people about this, right? These are things that are not taught in school, right? How do you actually go about making money? Right, and how do you go about building wealth and growing it? Those are critical lessons learned? And I know that you've done some I haven't seen it. But I've heard that you've done some things around education for younger people on this. Can you talk about that? And have you done it in the crypto area as well? Jerremy I have. So I came up with a book not too long ago called a stock stock market journey. How to make sure kids win at life every day. And in that book, actually kind of blend in the nuances of currency. And talk about money is a fluid discussion because I mean, it is right it's a universal language. It's something that it's borderless, money is and it changes from border border, oftentimes, but allowing kids to realize that this is like a video game, you have to learn it, you have to play it, you're gonna lose, just like in a video game that you're not always gonna pass the level or whatever you might initially. But as it gets harder you get to determined you increase your skills and your capabilities through that difficulty to come out on the other side proficient at this game. So my take is yeah, I've created a live course that I did in March. So March is kids month, every month in my company. So I did a live educational event for children. And after that, it was a week long and at the end I today an offered a mentorship program for children and their parents to go through with one of my mentors so that they can learn together. It's kind of like a like a spring break at night. Learn and just understand more of it. because my thought Aussie grant is not going to change your life, and are they going to become full time stock traders? Probably not. But they will start to see the world differently. And they'll believe different beliefs now, because they will see that money can be created easily doesn't mean that you always have to choose that route. But it's at least a choice that is available to you. Grant Yeah, I love the fact that you're you're providing that for for these people. You got an awesome mission. Okay. All right. Let me get back to successful crypto trader. What does that mean? How do you do that? Well, like what does it mean to be successful? crypto? Jerremy Yeah, I mean, valid question, I think, I think success. For me personally, I define the word success as the opportunity to recognize or did I recognize an opportunity, like, That's it, if I recognize opportunity, I'm successful, I made it easy for myself to achieve success. But from a monetary standpoint, I mean, like, if you're actively trading, if you're successful, you haven't blown out your account, right, you haven't lost tons and tons of money, you still have capital around, but you are able to increase your currency that you're trading with, to better your life or the life of others around you. That's essentially it. Right? That's, that's the, I would say, an ulterior motive of success is for people to figure out a way to help others with their success. Either teach it, provide it, give it away, donate it, expand it, offer it something. So if you're a trading and you're able to carve out metal sell something of the day, if you made $600 Extra, or you made a $600 profitable trade, so 600 US dollar increase when you do 200 days a year. That's $120,000. Extra. Like, that's bomba, that's the number three significant, so tour data of the year. So we're not even talking. This is a 24/7 365 job. There's like no 200. So you're doing it's a third of the week that you can sit in and look at a good trade every other three days you find a good setup, make 600 bucks like $120,000 extra year, that's magnificent change you have as life changing and up and people do have the opportunity grant all over the world to participate in crypto, because you can do with the euro, you can do it with the Japanese yen, the Australian dollar, the British pound, any type of currency can be transacted and use through crypto. So it's a really fantastic tool. Grant Do you have a favorite that you typically pursue or trade? Jerremy I do? Yeah. So one of my favorites. It is a theory a theory was one of my favorite Kryptos for sure. But also there's another one that's a little bit less known called Cosmos, which is, which is Adam and so Adam ATO himself spelled, Adam pays a 5% yield to kind of like, is it through Coinbase. So Coinbase is a publicly traded FDIC insured company at this point. And Coinbase allows traders to have a position and Adam and just receive 5%, just like it would in a bank well used to write well, you can just kind of leave your money in the bank and just get like a free 5% return on your interest or a CD or whatever. Pretty fantastic. And that's because it's a very volatile asset class and moves up and down a lot. And so when you're leaving your money on the exchange, the exchange of the broker is able to go back on their on their side, and trade and transact with it. Just like a bank will take your money entering transact with it's really cool. Grant With 5%. Really? Yeah. 5% ROI. Okay, so now you can take all your money out of your CDs where you're getting point 0.002%, right. Oh my gosh. That's crazy. That is That's amazing. So in terms of crypto platforms, crypto trading platforms, do you have I mean, you mentioned using Coinbase? Or what do you what do you use them? Jerremy Yep. So I can definitely give you a few, Coinbase is absolutely usable. It's really easy, super effective. I like it. A lot of traders like it. A lot of individuals use it, but it is more of a what I would refer to as like a longer term. For crypto, you don't want to actually try it. The fees are a little bit higher. It's a little more clunky. clunky in the sense of it doesn't have a lot of advanced features to use. So I do use additional advanced features and other cryptos trade platforms, ones called Coinbase Pro. So it's their upgraded version of their main platform. So you can actually trade you can set limits, you can set stops, you can do all the advanced features that you want and Then if you want to level up from Coinbase Pro, there's a platform called Kraken, K R A K E N. And all these exchanges are very easy to transfer the money back and forth. Kraken is working on an IPO right now, which is they're gonna come out in the market, hopefully in the next few months. So you have a lot of opportunities to anyone, right? This is here in the US. I mean, you can open up an account been an account and like four minutes, if you're bout technology, three minutes, if you're fast, it's really easy to use. It's super easy. You can download on the app store you can use on an iPhone. I mean, it's, it's available everywhere now. Grant That's awesome. What a great, I'll check out crack and I've used the Coinbase stuff. But it wasn't the Pro. And yeah, I came back going oh, clunky, slow. And I couldn't couldn't control my trades very much. And this isn't the Yeah, yeah, but it's good for longer term. Jerremy Like you said, the CD thing that's kind of what I tell people is like, hey, just treat like, essentially treat like a CD. You know, look at it, play with it. Like, have a have a long term, just you're buying slowly over time. Right? You buy and just sits there you treat like a savings account. Just keep buying, don't touch it. Don't buy anything. Don't do anything weird with it, just slowly buy over time. Let it accumulate, treat it just like a savings account of money come out of your bank into Coinbase great way to use it put into Adam get a 5% yield. Good times. Grant Awesome strategy, talking about strategies. And of course, your training material you do awesome talk talking about different trading strategies, do the typical sort of S&P 500 trading strategies that lots of people talk about? Do they apply in the crypto world? Jerremy Great question. Not fully. I mean, depends on what you want. Obviously, we're talking about but so crypto doesn't have very fluid option trading right now. So options are essentially insurance contracts where they protect your downside, help you leverage your upside things that nature. They are offer, but it's really more for international individuals right now. So the US is getting on board eventually with that process. However, long term strategies like buy the dip, buy long term, like take some money and accumulate over every few months. Absolutely. That works like so long, the longer term strategies that can definitely be effective and certainly be useful to think about some other ones. Just try to think of other like really aggressive strategies. I mean, I personally don't trade Kryptos on a small term timeframe. So I say small term, I mean, like, on a 15 minute chart or less. So I don't day trade Kryptos. And here's why Kryptos can very easily move 10% a day. Like that's simple for a cryptocurrency to do which is wild. But as I mentioned earlier, that's why people are interested in them. I don't go less than 15 minute chart because I don't want to capture a 1% gain or 1% Return on something that could move 20% When 10% On Tesla or Advanced Micro Devices or Apple, I'll trade those on a daily basis, but they're not going to move 10% A day 99.99% of the time. So I'm looking for one to 2% pulled out the market, right capture that cash flow, but on on Kryptos. I am more of what's called a swing trader. So I'm usually in for three to six weeks is like kind of like my preferred timeframe. Grant Oh, awesome. Awesome. Okay, so what about alignment with the s&p, do you see anything there happening between crypto and s&p alignment? Jerremy Ah, that's a good question, man. Yes, I kind of do actually. I've been noticing or at least it seems to me that Kryptos actually kind of leading the stock market a little bit. And the stock market as of right now has been a little bit of a laggard or a little bit of a weaker position. Not overall but in general, or specifically. So to come up with an example Aetherium and Bitcoin are down about 40%. Pay Pal is down 70 squares down 65 Facebook is down 45. Right. Netflix is down 75% Boston Beer Company is down 80% You have some companies are down 85% like Roku. I mean, some individual companies names are getting absolutely decimated. But big coin in theory, we're only down 30%. It's like well, relatively speaking, that's not terrible. And that's actually started before that wasn't like early November. And most of the stocks, the bigger names at least big broader market, s&p, NASDAQ they started selling off late November. So I kind of see Kryptos as almost as almost a leading approach like if I see strength in crypto, I'll have ventually assumed literally strengthened the stock market, sometimes at the same day. And I think that's because people are going to, again, slowly peel some money into crypto, the total market cap of cryptocurrencies on a like, again, accumulative basis right now is almost 2 trillion, 2 trillion now really? I'm sure Yeah, but but that's not a lot, right. That's the market cap of Apple, Apple. Yeah, that's one Google. That's one apple. Like, that's nothing essentially. So if you take, I think, I think there was a stat that said, the overall retirement savings in all of us, like, if you take the US, you take every single dollar in retirement accounts right now and average them together. It's like 36 trillion, which is a lot. If we take 10% of that 3.6 trillion, and put it into the crypto markets, I mean, crypto market triple, essentially overnight. So that's the grand your larger term I get at actual sizable money starts flooding into these Kryptos, they likely will go a little bit higher. And so that's why I kind of think that the crypto market almost right now leads the stock market. Grant It just looks amazing in the fact that it hasn't pulled back on such high weakness, I was reviewing some of the various stocks just last night that you were mentioning, and I was looking on the monthly charts, the the massive pull backs, and I started thinking, this is starting to feel like buy time. You know, when it's down this far back, you're like, wait a minute, this is probably what what's your take on that? Jerremy You're not wrong, man, you're not wrong. I do. I think that the way, there's a very popular term, I don't don't try to catch a falling knife. But my my definition of a falling knife generally is if you are trying to catch it, right, don't try to catch it with both hands. So keep keep one of your hands alive. So throw a little bit of money at it don't get super super aggressive. Take a little sizeable chunk so let's let's say have 100,000 our portfolio and unit put some money in the...
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CAIR 66: 7 Pillars To GROW YOUR WEALTH !!
04/16/2022
CAIR 66: 7 Pillars To GROW YOUR WEALTH !!
In this episode, we take a look at the seven pillars to grow your wealth. Grant Everybody, welcome to another episode of Financial investing radio. My name is Grant Larsen. And today I have in the house, one of those unique people that understands some of the fascinating ways to build and protect your wealth. I'm excited to have with me here today, Seth Hicks. Welcome, Seth. Seth Thank you so much Grant, glad to be here. Grant So when you reached out to me, and you started to say, hey, could we talk I started to look into what it was you're doing. I mean, I'm hearing words like private banking and asset protection expert, you hear some of that stuff? And you think, Oh, wow, do I have to have an advanced degree, right in financial management to understand this stuff. But what occurred to me is that I've seen some of these principles before, they don't seem to be well known by most. And so what I'm excited about is the opportunity through this channel here for you to continue to get your voice out there and say, here's a way that you can build and protect yourself. So first of all, how did you get into this? Seth Well, I practice law for about 25 years now, and have structured transactions, commercial real estate transactions, business, acquisitions, and sales. And kind of help people keep what they make, so to speak. And when I met my now partner, Vance Lowe, the principle of private banking strategies, it floored me to find how easy it was to make a few changes, and effectively do 100%. better job. And so what I mean by that is private banking strategies, we use whole life insurance policies that are structured in a way to have a high cash value, and in the appropriate structure and appropriate jurisdiction. They're statutorily exempted and protect it, much like a homestead in certain states and many of the same state. So, for example, in the southern states, you've got a post Civil War air legislation where... Grant It goes that far back post Civil War? All right, absolutely. Seth Yeah. So private banking goes back as far as Civil War era. And even before that precedes branch banking, it precedes the the type of current culture banking that we have. And the post Civil War era statutes protected their their citizens, the state citizens from Northern carpetbagging. So for example, yeah, for so for, like example, in Texas, and Oklahoma and Florida. And a lot of those states, south of the Mason Dixon Line, you have laws that protect homesteads. So in the event that there's a liability, and someone has a homestead that they've declared, it is 100% protected from being taken from them. And that was a product of the Civil War. Grant So let me ask you this, when you talk about how you know protection from having it taken, I'm assuming you're talking about scenarios like maybe bankruptcy scenario, or something else where you owe other people but you've got this protective layer that no one could actually come in and take that foundation from you. Is that right? Seth That's right. A lot of our clients, you know, higher net worth, some of some are ultra high net worth, and many are blue collar, but they have created strategies to keep what they make. I mean, no one wants to effectively work hard to earn money and then and then lose it. So those type of folks who gravitate towards structures where they're able to keep what they make, so for example, if you've got a homestead You're in Texas or in Florida, and you want to use it as a vault, and you don't have any debt on it and you're able to pay the property taxes, year after year, then it is 100% exempted from creditors or from outside taking. Grant So that's an important baseline is that it does need to be debt free, you have to have no mortgage on that or any liens against that. That'd be right. Seth Sure, yeah, you've got to if you've got a, you know, a loan with a traditional bank, they have a right to the mortgage payments or, and so they will effectively if not paid, foreclose on that, and those rights are obviously superior. But if you're if you're in a position where you're able to, for example, use your own private bank, through the cash value in your own policies, and purchase and acquire your home, or other assets through that entity, you would do the same structure, you mean, obviously, your bank and part of the cycle is getting the money back. And that's something that the Vance prides himself on his teaching people how to get the money back, you've probably heard some of that, and your private banking, that's one of the reasons that people do it, they effectively take the banking equation back into their own law into their own become the bank. Grant So as the flow is something like this, you get one of these Whole Life policies, it takes some time for you to build up some cash value, but then that cash value becomes something you can leverage and use for either purchasing other assets or leveraging it and other investments, so to speak. And that has some protection wrapped around it, is that what you're describing? Seth That's exactly what I'm describing. And like I said, a lot of our clients are higher net worth or even ultra high net worth. And when they capitalize their bank, they are, they're able to do a lot more with it right out of the gate. But for the blue collar guy, you're right, it's a, it's a steady increase that you use. A lot of folks use this as a retirement strategy, because the ins and outs are not a taxable event. And if any of the audience wants to dig on that it's internal revenue code 7702. And what that basically outlines is that your whole life policies, your your cash in and your cash out, are not taxable events. So compare that with like an IRA or a 401 K, that someone's been socking money into. When you take those distributions. Well, if you take them too soon, you're penalized you penalized if you take them too late, you're penalized. Yeah, and it would take them right in that the right time. You're still paying taxes, I'm still paying taxes on it. Grant So every single cash transaction on the cash value, no tax, no taxation on that, right. That's, that's amazing. How blue collar person or someone that's not old truck, how do they get started then Is it is it I hate to say as simple as but Is it as simple as getting started with your whole life policy earlier in your life than later? So you can begin building out that cash value is is that the number one thing are what else would you do? Seth You know, I wouldn't say age is the number one determined to factor. In fact, we've got an article and a podcast that we've produced that says, you know, you're never too old to start private banking. And here's why. And we go through the outlines the benefits and values, which include asset protection, tax free growth, financial privacy, no taxation on the legacy value. So if you're leaving high value to heirs and benefits, beneficiaries, don't pay any taxes on that transaction, even if it's ultra high. So there's some value there, depending on what your primary motivations and focus are. And the age of course, if you start earlier, you're going to accrue a much greater and higher value as you you know, as you go year after year, but let me give you an example. We've got one of our favorite clients is as a woman in Texas, who was a single mom, and she started out with a $5,000 annual whole life policy and she made she made that contribution for a few years and and then use that cash value to as a downpayment into an investment property. Oh really? So she purchased this investment property as and then she also had third party financing of course, she began to develop cash flow from that and she paid her bank, her private bank back and as that cash value increased in a crate increased, she did The exact same thing, she rinsed and repeated the process with the second investment property. And now she has a million dollar equity portfolio in real estate from where she started at $5,000 leverage. Now, we've been, you know, she's had the benefit of an appreciating real estate market, she's had good investments, but it illustrates the principle that you can actually start in that small of an amount and and multiply that seed into something that really brings a large harvest. Grant That's fascinating. One of the things I noticed from you was, I think you call it the Seven Pillars of private banking strategies. Can you speak to that for a moment? What are those? Seth Sure, the first, the first pillar we've been talking about is asset protection. And the second pillar is tax free growth, which is we also referenced that compare that to a 401 K, or an IRA, you may have tax free growth inside, but you're going to pay taxes when it comes out. And we've got some illustrations that kind of compare those two things and show you you know, which comes out ahead, and it may look like a contributions from an employer and other matching proceeds will come out ahead. But in overtime, they really don't. So you've with inside the policy, you've got compounding growth, and you've got a tax free growth. And you've got a financial privacy. third pillar is financial privacy. Whereas compare that to a bank, for example, who has to KYC know their customer, know your customer, they want to understand, you know, every aspect of money in and money out, you going to try to take out or put in a large cash, for example, a 510 $1,000 Cash, I'm into your Wells Fargo or Bank of America account. And they want to, you know, cross examine you on 50 questions about why you're using cash, where, you know, that doesn't happen in a private contract with the life insurance companies, we use it, it's totally private, and they don't raise their hand and go, Hey, there's a large transaction in or out, and they're not required to by the IRS Code 7702 Grant And it's just not part of their business model, right? Seth It's not part of their business model. No. And so it's interesting to point out this is kind of a little sidebar, but the largest players are the largest clients of the life insurance companies, or the centralized banks, like Wells Fargo and Bank of America. I think the last time I looked at Wells Fargo has a 20 plus billion dollar annual premium for life insurance policies that they hold on employees and, and others. So if, you know, gives you some insight. Grant That's huge. Okay, so right, so asset protection, tax free growth. Seth Tax free growth, financial privacy, privacy, the big one is velocity of money. And once philosophy of money, we describe that a little bit and in the the example that I gave our audience with the woman who started with a $5,000 premium, and then when she had enough to make a down payment on an investment property, she did so and so she she paid a premium dollar into the whole life policy, she borrowed that same dollar out to make a downpayment, she purchased a piece of real estate with that dollar, she got a rental dollar back from the tenant, and she paid her bank back on the note and deed of trust. And that's the velocity of money. It's the multiple touches within your own economy of the same dollar. And I mean, I'm simplifying it there with $1 but that's effectively the transaction. Grant Now that like you said earlier, it's the rinse and repeat principle right meaning absolutely cut it out. She's liquidated it used it acquired some capital back repaid herself and now she's she's reset to do again, right? That's absolutely. When every Seth When every dollar that she pays back into her bank, Grant, it increases the cash value, dollar for dollar. So you've got that that loan from your bank coming out. And when you recycle that rental cash flow back in or that business cash flow, or that cryptocurrency sell, or whatever your investment might be back into your bank, your cash value goes right back up to whatever you've put in. And so you and I both know that banks they make money by lending money. So Wells Fargo with and Bank of America orca Chase and these large centralized banks, they put their money to work by making good loans. They make loans that are secured, they make loans that are collateralized. And they, ultimately they want that cash flow with an interest rate. Well, it's the same principle with your own private bank. And you want to make a good loan to the borrower, whether it's your business, whether it's your brother, whether it's whatever a third party, you want to make a good loan, make sure it's collateralized and secure in the chief got an investment, cash flow, and an ROI on that loan coming back to your bank. And there's that cash flow increases again, you do the same thing. So you begin to think like a banker, you think like a banker? Grant Yeah. Because that's so liberating, right to people to be able to be on that side of the table. Right? making those choices. Alright, and then what's the fifth? So there were seven? So I was four. What's the fifth one? Yeah, I'm looking at the seven pillars. Seth So guaranteed financing. Yeah, it financing. So let's say that you're that you've you've you've done like our our hypo example with a woman there. And she's gone through a number of years, but she only started with 5000. Remember, now let's say that she's got 100,000, in total cash value. And she's in a state like Texas, where you can buy an investment property for 100,000. Or she could lever into multiple properties on like an 8020, split, for example, you know, she could buy five properties with 20%, down and put 20,000 down on five properties that cost $100,000, financed the other 80%. And she's building cash flow on all five of those, and actually getting a much higher ROI. And in that example, what you what she would be doing was effectively using leverage to increase the ability to invest in multiple assets. And when her cash value stacks up high enough, she could take out the third party lenders, or she could continue to use that strategy of leverage. And that really depends on someone's their own risk tolerance, their own investment strategy, some folks, they you know, that they're going to eliminate those third party loans. And they're going to take that cash value and just totally take out the third party debt. And so the only debt that would remain on that particular real estate asset would be their, their own private bank. So the guaranteed financing part means you don't go to the bank, and you don't have to qualify, you don't have to go through any type of you know, yeah, because you're the bank. Yeah, you're the bank. Yeah. So you make sure you look that guy in the mirror, and you make sure that you're making a good loan on a good asset. And you do that. So but I described the principle of leverage, because a lot of times people get ahead on that concept of leverage, as opposed to just buying one property for $100,000. And let's say you're making 2000 a month, you got 24,000 in gross cash flow, versus, you know, if you spread that across five properties, and you got 24,000 times five life and cash flow, so you know, and you're able to just knock those debts out a lot faster. That's the velocity of money and guaranteed financing working together. Yeah. Grant And written replenishments faster. Okay. All right, number six, and seven, what are those on your seven pillars? Seth So guaranteed compounding it tax free growth is the part inside your policy that that cash value and your premium dollars, they are compounding inside the policy annually, and there's no taxable event. And so I think it was Einstein who said the, you know, the compounding interest is the eighth wonder of the world or something along that line. And if you're not, you're not getting compounding interest, then you're making a mistake. So you don't get compounding interest in your centralized banks. You don't get compounding interest in various other investments or formats. But in this these policies you do. So that's, that's something that is very distinguishable and it also takes out the market risk with your policies and the values in there, you're not subject to market risk. So this is not universal life. This is not indexed. Universal Life or any type of risk transfer. To the the owner of the policy or to us, you're not taking on market risk. But in those types of policies Universal Life or index, Universal Life, ual Grant You, you are taking on market risk and one of the things? That's right, so being in control of the risk, right, that's absolutely mental aspect. Seth Absolutely, if you're going to use your cash value and put it to work and investment, you should be the one that's able to identify that risk and not have it subject to equity market risk. So it never goes backwards, you're going to only see a steady prodding forward with this compounding growth. And after a certain number of years, it starts to go more parabolic. And that's, that's really the beauty of this. And the magic of it. Some folks, they they locked this stuff up for retirement strategy. And you know, some are using it for the leverage. Grant Yeah, you know, it's interesting, I've seen some financial people describe that risk control paradigm with a with a pyramid, right, and they'll describe it, you know, in the, in the manner that you want to have more control. So you start, you start, you should start these sorts of strategies first and get that established. And then and then over time, as you go up the pyramid, you have less control over it higher risk, potentially higher returns, but that might be where you're doing some you're, you know, trading or investing or self directed activities. And a lot of people invert that pyramid, right, that's a well, they'll start with that self directed trading or investing. It's, you know, high risk, low control, and then blow out what capital they have, when instead, turn that the other way around, start with these foundational approaches that you're describing, and then build on top of that. Does that make any sense? Seth Amen, absolutely does. Sometimes will, will describe that as, you know, Hare and tortoise paradigm. And some people go, Well, this isn't, you know, I can make this much here. And I make 12% Over here, I can make 15%. Well, no, you really can't over 30 years, and likely there's going to be a risk factor there that may blow you out. Totally. Grant Yeah. And the loss of control that absolutely, yeah. Now. Yeah. Seth I mean, you've got this third party risk, whenever you've got, you know, a transfer of your money to someone else. That's, you know, you've got that risk that counterparty risk, whereas this, these insurance companies, they don't fail. I mean, they've been paying dividends, since before the Civil War, year after year, through the Great Depression through the Civil War through every economic upturn and downturn that there is. And it's, it's just one of the reasons why grant is because there's a cash reserve requirement of one to one, as opposed to a cash reserve requirement at a Wells Fargo of maybe 10% or less. Yeah, so they take they take $1 In deposit, and they're able to lend out 10, or perhaps even 50, depending on what their total asset bases and that's, that's funny math. You just print money out of thin air, and then they're able to loan the printed money at an interest rate, and they're making money on something they never even received a receipt. Grant Fascinating, right? The before I ever heard about this approach of this technique, one, I have to tell you my origin story of learning about this for the first time, it was my wife was driving our minivan. It was when our kids were little. And she was backing out of the garage and kids were bouncing around everywhere. And you know, I would have made the same mistake, but she wasn't watching. And she was turning around and talking to the kids. Hey, kids sit down, she backs out and just wax the mirror off of the side of that house right on the...
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CAIR 65: How To Win So You Can GIVE BACK !!
04/02/2022
CAIR 65: How To Win So You Can GIVE BACK !!
Grant Welcome everybody. In this episode I speak with Jerremy Newsom who has a system for giving back Everybody welcome to another episode of Financial investing radio. All right today we have in the house. Mr. Jerremy Alexander Newsome coming to us all the way from Nashville, Tennessee. He is a long term successful investor and trader and he's been gracious enough to spend some time with me today, talking about some of the unique things around what he has done and how he's benefiting the market and investors and traders. So first of all, welcome Jerremy. And please take a moment to introduce yourself. Jerremy Thank you so much, man. It's always an honor to pour into like minded individuals I love that everyone here is interested in investing and growing their minds and therefore growing their bank account. My name is Jerremy Newsome. It's spelled with two R's. My dad's name was Jerry. So it stands for Jerry and me. That was Oh, that's awesome. Thanks, Mom. Yeah, man, I love the stock market. I love trading. I do love investing, right? Everything from long term buy and hold to day trading options and everything in between. I think that the liquid markets are extremely fascinating. And one of the things that I spend the majority of my time doing is helping other people learn how to do it themselves, right how to generate cash flow, using the markets, so that they can live the life that they want to live and help me people they want to help. Grant I love that. So one of the things that triggered me to want to be able to talk with you is when when I had the opportunity to interview I was looking at something about you in your background that sort of caught my eye in terms of what you started with. I'm not gonna give it away but would you back up and just talked about how this all got started? How did what got you thinking Let me do trading. Let me do investing. What was it that can get us that sort of the beginning? Jerremy Yeah, dude. The craziest thing it was a movie, a Tom Hanks film 1994 Academy Award winning film Forrest Gump. And I was watching that at six years old. And I was watching with my dad and my oldest brother, Jerry, Roger. And by apresenta way through the movie, Forrest Gump says that him and Lieutenant Dan invested into a fruit company and they no longer had to worry about money anymore. So I asked my dad, I was like, what is the fruit company was investing because when I mean we were poor, financially, we were very happy family had a great incredible childhood. But we were very poor. We we were at the time living in a single wide trailer tree house. Doesn't. It's not nearly as glamorous as it might sound. What I mean, okay, a tree house. A bunch of single wide trailers thrown into a tree house. Yeah, really? Grant Wow. That's a story right there. Jerremy That was a story. My dad was a creative builder. And I lived in there for from age three until 12. And so anyway, we're watching this film. I connect with that because I was like, Well, I would love to not worry about money anymore. I know a lot of my family members or somebody that we stressed about and worry about. I would like to not have that be an issue. When I asked my dad what's investing what's the fruit company? My dad goes on to tell me about Apple and how the stock market works I was like let's do this the Forrest Gump investing model Dad Come on, let's do it. And you know, he did the normal dad routine, right? Like yeah, this is a movie. Yep. It's but I asked my dad was like, Is Apple a real company? Can you actually invest in it? I begged him and begged and begged him and he said, Listen, if you bring me some money, I'll match it dollar for dollar and we'll buy some shares of Apple. So I went and picked blackberries, door to door and made 1500 bucks in the summer of 1994 some blackberries. And so true to his word. We bought $3,000 worth of Apple in 1994. Grant Man you bootstrapped it. I loved your initiative. Uh, you know, the fact that you really wanted it you went after sold blackberries, right? Like, we just want to pick them out of gardens kind of thing sold and door to door. Jerremy Yeah, yeah, just exactly. So they grow wild in South Georgia. And so I just walk around up and down the streets and find BlackBerry pouches and put them in plastic bags or buckets or whatever. I could find them and just wrap them up and then go to go to Door Door and sell them. And the thing is, though, I sold them $1 bag, organic handpicked blackberries. 35% cheaper than they sold stores and had a six year old no shoes, no shirt jean shorts at a high closing rate. Yeah, grandma's would give me 10-20 bucks. You know, I think I was cutest thing in the world. And that was it. Grant You know your audience? That's awesome. Yeah. But you know, your dad's brilliant to where he, he saw that. Hey, you know what, I'll support you in this. But I also want you to take some ownership as well. I think that's a great, great learning, right for your kids. Jerremy I love that you brought that up, man. You're 100% Right. And I'm assuming that you're a father. I can probably I can make... Grant Six kids six grandkids actually two more grandkids, almost eight grandkids. Yes. Big family. Jerremy Good for you, man. Good for you. That's incredible. And yeah, so you're absolutely right. It was an ownership thing where it's like, Listen, you want this bad enough? Prove me how bad you want it? And I did. And then he Yeah, he was true to his word. Grant Big time. I love that. And I know, I know, you've mentioned this before we got started. But I feel like this is this is the right time to bring this up. You just released something for kids phone is that? Jerremy Ah, yeah. No, thank you, man. We talked about that just a few minutes ago. You're absolutely right, I have a brand new book that just hit Amazon. That's the only place you can buy right now. I'm sure it'll be in bookstores eventually. But it's called a stock market journey, how to make sure your kids win every day in real life. And so if you just type in stock market journey into into Amazon, you'll see a pop up and a man. So that's it's a stock market education book for kids, which is very rare. And it's more or less like it doesn't exist. I was told by a person forever ago, like a business mentor. Don't do that. Don't waste your time. There's no demand, like kids aren't trading stock market. Like why teaching? Yeah, I was like, Well, I want to know. I mean, there's someone else wants to know. Grant Yeah, you're absolutely right. Absolutely. Yes. Yes. Some of my own kids have done that as well. So I love the fact that you created that book. Okay, so So backing up here. So you have this experience you you got the got the edge, got the bug, committed your time, got the apple investment going. Alright, you've got this sentence in your headshot piece, who shared to me I love it says retiring on $3,000 how to grow a modest investment into a comfortable retirement. But that tells me as you're thinking about us as people in general, right, you're not looking at Gee, it's gonna take lots of money to pull this off. If you do it right. You can bring you can lower that bar to get going with this. Can you talk about this? Jerremy Yeah, so essentially, I teach people how to leverage their funds to do day trading, and to be in a position where they're comfortable, where they're not risking insane, insane amounts of money. Because you can leverage money very easily, right? Money is the easiest asset to come by. Now, most people don't think that's accurate, especially if you're not extremely wealthy. But it is like like, if you buy a house, you didn't have to come up with all that money. You went ask the bank and the bank gave the money. And so now you're paying the bank back plus interest, but you are living in a house and 100 or 200 or $3,000 that you didn't have to come up with up front, you got the money, right? That's a resourcefulness going out and getting a bank. But there's other ways to get houses, owner financing, asking your parents, whatever, right there's a million ways to buy a house. So for me when it comes to actively trading the market, most people don't know that leveraged funds exist. And when they hear leveraged funds, like I'm about to lose all of my money. There are mathematical formulas. Second grade math, I'm not very smart at math grant, I'm like a, my IQ is a high 93. And I use second grade math over and over and over to ensure that I never lose more than 1% of my account on any trade. So for me, you can take $3,000 And you can actually get access to $100,000 in day trading, buying power right using the leverage funds and only lose 30 bucks per trade and 30 bucks per trade is 1% of $3,000 Even though you have leveraged $100,000 available so it's it's incredible what's available out there and I wrote a book also called money grows on trees, teaching people these concepts and letting people know that this does exist items and processes And then, you know, companies out there know how to use their money and how to leverage it and give it away for people who might want to grow into a substantial sum of money. Grant So that's interesting that, you know, you identified putting that risk management in place upfront that that seems to be sort of the common theme across a lot of traders that are real successful and having the discipline to say, You know what, I'm not gonna go past that $30, and I'm gonna diversify this, is that the basic strategy across a lot of different trading positions in different markets? Or how do you approach it? Jerremy You're not incorrect. That's absolutely one way. Another way that I do it is you create the calculation ahead of time, so you have your 1% of your portfolio. And for me, I'm taking this from a active trading perspective. So I say active trading, I'm a full time legit, professional stock trader, and I'm in front of the computer, trading maybe 10 hours a week, maybe during the time I'm studying, I'm reading I'm listening. I'm doing podcasts I'm, I'm talking people much smarter and much wiser than me like you asking them, Hey, what are the macro economic challenges are going to face America because of Ukraine or because of COVID. I'm asking other people things that's using them some spending, most of my time doing is listening to veterans, people have been doing this for 20 3040 years, getting their their knowledge and their expertise. So the math, for example, is let's say you have a $3,000 investment. 1% of $3,000 is $30. Well, the math behind the risk is if you buy Apple at 180. And you're like, Okay, if Apple goes down to 179. Get me out. So you're risking $1? Well, if you know your risk is 3030 divided by that dollar equals you can buy 30 shares of Apple. So even though your investment in this scenario is well over $4,000, you're only going to lose 30. If it doesn't work. Now, let's say Apple goes from 180 to 190, you make $10 per share risking $1, right you your risk reward is 10 to one you just made $300, even though you only risked 30, that 300 bucks. So it could be cash flow grants could be huge for somebody, right? That could be a car payment, that could be an electricity bill, that could be all forms of items that they might need. That could be groceries, and that could happen in an hour. Right? Like that tray could happen in an hour and or 15 minutes sometimes. And it's amazing how quickly the markets can move. Grant Yeah, it is amazing. And with that sort of control risk, and that potential for upside being much more than what the risk is you're taking on. So you're leveraging options, It would be my guess to do something like this, is that right? Jerremy You absolutely can leverage options. And I do and I know how I'm very versed in options. But I do generally 99.9% of the time instruct most of my clients to start with stock because it's easier. And stock margin and startup stock leverage is super, super available to anyone who wants it, essentially. And yeah, it's amazing what's available out there. Grant That is amazing how long then you typically in positions as you help people do this. So so your your coach student would be one that would come in take your system, they're in front of the computer, they're leveraging their their $3,000. And they might be in a position for like you said 15 minutes or an hour. It's certainly shorter timeframes, right? Not they're not holding anything overnight, or do they? Jerremy Very good question. Right. So the leveraged accounts to leverage trading, this is a day trade system. If you're going to hold overnight, I almost never suggest using leverage, though. If you have $3,000 to your name, like you're going to put $3,000 in you're only going to invest, right what you can afford to lose if you're going to hold for long periods of time. And so yeah, absolutely, man, this is a day trade system. But I do I love long term investing love long term. It is an incredible way for wealth generation and for asset appreciation. But I think day trading is really cool for cash flow, right? Because investing is like Well, it's great, but now I'm 65 What now? Well, what if you're 33? Or what if you're 29? Or what if you're 48 and you got a few $100 or 10s of 1000s or a few 1000 And you're like well I would like to make $400 Next week though Can I do that? I was like yeah, that's that's day trading there are systems available that can do this. Grant That's That's fascinating. So so with the the talked about the difference between fear and greed, those doggone emotions, alright, what's the secret? sauce here. Jerremy, how do you control those? Jerremy Awesome question, man. So good. I mean, it's, it is controlled to an extent, but it's also a lot of self knowledge and introspection. Because, for me, I don't believe that most market participants are greedy. Now I know that's a very, very popular term, right? I mean, Warren Buffett says buy when others are fearful and sell and they're greedy. And so on and so forth. There's a lot of the markets are controlled by fear and greed. There's tons of fear and greed baked into the system. But here's the challenge with that is inherently, the majority of market participants don't want to be greedy, right? They're God fearing church, attending people that are 57 with, you know, a few kids maybe a grandchild or two on the way, and they want to give to charities, and they want to donate and they want to help build orphanages and, and hospitals. They want to donate money to the zoo and protect pandas. Like, if you give money away, Grant, by definition, you're not greedy. Mm hmm. Yeah, I mean, I'm sorry. But that's like just the exact opposite of greed. You can't give money away and be greedy. It's impossible. So therefore, what we do is if people tell themselves, I'm greedy, and greedy and greedy, they're not going to want to make any more money. Because nobody wants to be greedy. So we have to remove these really weird, crazy subconscious beliefs that we have internally about money and about growth. I call it financial optimism, or monetary zealousness rather than greed. Yeah. Or money. Grant What about on the other side? Jerremy, what are your thoughts there around fear the management of that? Jerremy So fear? I mean, that doesn't go away. And fear comes down to having more and more certainty. That is a piece of it. So you do not have education? Thankfully, there is a company out there that teaches you for free, which is my company, I don't charge anything for these systems, or this education for this knowledge is I just gave it away. Grant I mean, you don't charge? That's amazing. You don't? Jerremy Yeah, no, it's totally free. Because I want people to be able to experience it, and to understand it, and to learn it, so that they can really figure out they want to do it or not, or to what level because if I'm being honest, I've made a lot of money, millions of dollars in the markets. I'm good. You know, I don't need anyone's money. Specifically, I love money, I'm not pushing it away, I'll absolutely charge you for things. But education is not one of them. I feel like I feel like education should be free. And so I create a free platform, people can learn my system entirely for free. And the piece of the real massive distinction that you're giving about fear is it is a knowledge thing. A lot of people are afraid of I'm just gonna use guns as an example. Okay, well, I grew up around guns, I don't have many, but I'm very comfortable knowing that if I hold the gun, how it works. Yeah, and I know how to put a safety on, I know that it by itself isn't harmful. Just like a car by itself is a harmful you put a drunk driver behind that vehicle. Now it's a weapon. So weapons aren't. Money is a tool, right? Money is a it's like a brick can be thrown through a window or it can build a church. Same thing with guns into the car are all tools. And once you understand more, you have more certainty, you have more education, that fear will slowly start to dissipate. And it won't go away entirely forever. But you will have and you'll replace your replace that with different fears over time. Grant Oh, that's awesome. I love the altruistic aspect of this. It's sort of a gift back and feels like what you're doing right to the community. Right. Okay. Let me let me improve the education of people. I actually think that Well, let's talk to the other side of that. Then, with that giving back can you speak to what are the outcomes been to your audience and the people that have gone through the systems? Can you speak of successes and things where people have had their lives changed? Jerremy Yeah, man. I mean, the first one that came to mind is a really good friend of mine. His name is Matt DeLong. He's actually my business partner, mentor of mine, when my best friends he's a little bit older than me. 45 years old, has two kids. They're both in college and he was a business owner. A little bit of money, started day trading and losing his face. I mean, he was hemorrhaging money, because he had no idea what to do. Just just losing money all you click the button, boop. He's gone by because there was a siphon. And he didn't know what to do. And so he pumped the brakes. He said he sought out assistance, a coach and mentor and he met with me and pay me for my time said hey, man, I'll buy some food or whatever. Let's let me Cafe this out. So come full circle. That was four years ago, four and a half, five years ago, he now can trade profitably consistently and have an income. And now that his kids are out the house, he is fully financially sustainable, where he doesn't have to draw off of his retirement or he, you know, he does not working right, he sold his business. Him and his wife are able to foster children well, and to be a real force for good by going on mission trips, and by donating to charities and him and I ended up creating a foundation together called Real Life Foundation. And so one of our main goals is to end human trafficking. And so we donate hundreds of 1000s of dollars towards that foundation, and we just we work on Yeah, man. Yeah. So he has time to pour into the world using his gifts and his skills tests with your technology, because he doesn't have to be working 70 hours a week anymore behind the desk, which that was that was the case. That's what he's doing years ago. Grant Yeah. So it's interesting. You mentioned what's called Real Life Foundation. Yep. It sounds similar to as it Oh, you are like operation Underground Railroad? Jerremy Yeah. Yeah. So that's, that's our main as who we support as one of our main go to . Like we do the in human trafficking by connecting directly with Tim Ballard. Grant Yeah, that's awesome. Wow, Jerremy, that's, that's really, really cool. Okay, so you're going after leveraging the benefits from this investing and trading strategies, you're tying it back into, I see two huge...
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CAIR 64: How To Systematically Grow Your Portfolio
03/12/2022
CAIR 64: How To Systematically Grow Your Portfolio
Welcome, everybody. In this episode, we learn the secrets of systematic growth for your portfolio. Grant Okay, everybody, welcome to another episode of Financial investing Radio, I'm excited to have in the house with me today, Mr. Adrian Reid coming all the way from Australia, which is fascinating to me that I have this opportunity to get connected with this professional trader on the other side of the planet, literally from where I'm sitting at the moment. First of all, Adrian, welcome. Adrian I'm thrilled to be here. Thanks so much for having me on the call. And isn't this just a fantastic part of the world? You know, we we can communicate from the other side of the world we can we can help traders from all over the world. And there's just really no boundaries now. Grant There really isn't. I love that. And what I love is your willingness to get on and share tidbits and insights, right to help the everyday trader who's really trying to figure out how can I grow my portfolio in a way that's going to manage risk? And I know you've got some excellent insights on that. But before we get into that, would you mind stepping back and sort of thinking, what's your origin? How did you get into trading? What even brought you to that part of the world at this point? Adrian Yeah, absolutely. Sure. So I've been trading for about 20 years or so now, plus or minus, let's say, six months. And What first got me interested in was actually well, before that, well, before that, my family had a board game, in, in our holiday house, called the stock market game. And I have these amazing, fascinating memories of playing the stock market game becoming a paper billionaire by going around the board and buying lows and selling highs and collecting dividends and stock splits and all of these things. And it was just fascinating. Like, oh, this is this is the best thing ever, was my recollection as an eight year old. Now, I didn't trade or invest for a long time after that. But that was sort of my first memory of the stock market. Wow. And when I started work, I pretty quickly came to the realization that I didn't want to be in the corporate world forever. You know, I was commuting. I was working extremely long hours, I had a lot of high stress right from day one of my first job. And I said to my dad at the time, oh, it basically is this one. It's like, Aha, yeah, I don't want to do this forever. So what do I have to do to not have to do this forever. And we talked about investing, and we talked about stocks and the stock market and real estate and other forms of investing. And so I just started down that, that journey. And when I first came across some money, you know, from from work, I started, I started buying stocks. And I did the typical thing. You know, I didn't actually know anything, but I didn't know that I didn't know anything. So I bought stocks in companies that I recognized that I thought were big names, good companies. Grant And now this is gonna go up, right? Adrian Yeah, yeah, this is gonna go up. This is a great story. And there's a big company, um, you know, I recognize that this is gonna work and I'm smart. So therefore, I should make money. And of course, what happens? You know, I bought in exactly the wrong time it went down. I lost money. Very, very cool at the peak, right? Yeah, yeah, absolutely. And so I look, I played around with that for a period of time. And it took me three years of trying lots of different styles. Before I actually started making money on it in the corner. I tried that fundamental animal. Grant First of all, that's impressive that you were able to, so you didn't trade to the point where you lost all your capital, right? You are at least wise enough not or did you at times, say hey, I blew it all out. I gotta rebuild. Adrian Oh, I had no look. Absolutely. I have never blown up an account. So when I think one thing that I've really got, that I did well, from the very beginning was always very cautious about risk. And this is critical, right? Because if you blow up your account, the problem is you've got to then go back to work, you know, save money, and that takes time and You've got to build up the courage and that takes time and you're gonna put the money in the market and and then try again. And then chances are you blow it up again. So as soon as you blow up and lose your money, you've just wasted months and months and months. So from the very beginning, I took small trades, small positions, low risk. And I had learned a little bit about risk control from some of the books I read. And for three years, I was able to survive and on my account sort of went sideways and down a bit and sideways and down a bit, but never really made any gains. But the thing that turned the corner was I, I read a series of books called Market Wizards, which no doubt you've read or seen. And Market Wizards is fantastic, because it's a series of interviews with professional traders who have done extremely, extremely well. And as I was reading through it, I realized that all of these traders have their own unique style. And some of them really were like, really resonated with me. And some of them were like, it was an alien from another planet. And what I realized by reading through those interviews is I had to find a style that really fit me suited my personality. And the one that resonated, the ones that resume the most were the systematic traders, the ones that have rules and did tests to check those rules worked, and then followed those rules. And the reason I resonated is because they didn't spend every waking and sleeping hour staring at the screen. Mm hmm. They spent 15-20 minutes, 30 minutes a day running their rules, placing the trades and that was it. And that's what I needed. Yeah, because I was working a job I you know, I didn't have enough capital to live on my trading back then. Yeah. And so I started trading systematically. And you know, I took three months off work to develop my first trading system. Grant Really? Yeah. So you took some sort of sabbaticals? Adrian Yeah, I just I just said, Look, this is, I want to do this. And so I took three months off, and they my boss basically laughed at me and said, Good luck with that, you know, trading. Okay. Yeah, right, right. So I didn't get a whole lot of support them from from anyone else apart from my wife and my family. But you know what, when I implemented my first trading system, my results basically turned around on a dime. So if you look back at my equity curve, you can pinpoint to the month where that trading system went live. And that's because all of a sudden, I was consistent, and profitable, I had an edge. And from then on, it's just a matter of patience, of continuous improvement, and adding capital, and then eventually to get there. Grant So let me ask you this, in terms of the trading system that you've developed and matured over time, what's your general timeframe? And are you in your positions for a few days? Several months? I mean, what's, what range do you trade? Adrian Yeah, this is a good question. This comes back to the idea of it's got to fit your personality. So I'm a fairly patient sort of person, I don't like frantic activity, I don't like you know, really fast paced decisions in high stress. So I'm, I'm a longer term, sort of hold. My my favorite style is long term trend following. So that could be I could be in a position for many months. But I'm quite, I'm quick, systematically to cut my losses. So if I if I, if I enter a trade and hits my stop loss on day one, I'm out, I don't care. I'm very comfortable with that. So trend following is my natural kind of place that I gravitate to. But I have shorter term systems and mean reversion systems that are quite short term, because now having evolved as a trader and got comfortable with what the markets can do, and how they move, I can trade other styles outside my sort of natural center, if you like. Grant So the key for us is to establish that main style of trading get good at that make that consistent, once you've got that producing now look at considering other styles that I hear you right? Adrian Yeah, absolutely. Yeah, absolutely. Absolutely. Because I think as humans, we, we have a natural sort of center or personality or style that will fit best with us. And let's face it, trading is kind of hard, emotionally. And so if you're, if you're challenging yourself with a style that doesn't fit, and the market is challenging you with all of the, you know, the volatility, the ups and downs, the uncertainty, it's pretty difficult to stick to the rules. But if you have rules that are somewhat natural for you, they fit you and you follow them, then you can learn all the emotional essence from the market deal with those and then branch out. I think that's key. Grant Well, so earlier, when you made the comment, hey, you went to your corporate job, and it was stressful. The thought that went through my mind was trading can be stressful. So what is it that protects you, right? It's a different kind of stress. How do you equate the two stresses? I've got corporate job, let's say and their stress is there. But wait a minute, I've got training in the stress. How are those different In your mind, Adrian I find that different, the types of stress are different in terms of the duration, intensity, and how much control you have over it. So in the corporate world, what I found was, I was just under constant pressure to do more and more and more and more and more and more, and anything that I could produce, the corporate machine still wanted more. And if I wanted to perform even better next time and get a bigger bonus, then I had to produce more. So it was relentless. Whereas in the market, and it's also externally imposed, you can't do much about it, apart from resigned from the job, if you no longer like it, you know, it's sort of outside your control is what I think you don't feel. I felt that way. Now, in the market, the market is also outside our control, we cannot control the market. But we can control certain things which are really, really important. We can control whether we are in the market or not. And we do that through our system rules that we trade with, we can control how big our positions are. So that whether or not the volatility causes stress or not. So if you position size very aggressively, you're going to have more stress and more stomach acid in your life. If you position size conservatively, you're gonna have less. So we can also control what strategies we use. If you're long, lonely, and you're highly leveraged, it's going to be amazing and pretty stress free in the middle of a bull market, that the end of a bull market as it's turning, it's going to be extremely stressful. But if you're long only, you don't use that much leverage. And you've got some some short term systems and some long term systems, and you can make money from a bear market. And you can make money when the market turns because you've got different strategies, then some of that stress is really dealt with, because you're diversified in a way I saw. Grant So if someone's new to trading, does it make sense for them to approach it that way? From the beginning? Or do they still need to get really good at say, their first initial personality style related system? And then over time, then build that more equitable approach to trading? Adrian I get really good question I, I think the answer is you've got to start somewhere. And in order to start, you've got to make sure it's not too overwhelming. So I would say start with one system, or one strategy that you can quickly build confidence with. And it really helps to have a guide to kind of step you through that. But if you've got a like someone to model or someone to follow, you can quickly move from one simple strategy to a diversified portfolio. And so, you know, I teach traders and I teach a lot of brand new traders, and I've taken people from knowing absolutely nothing to a very diversified portfolio in a couple of months. So it really is just, oh, wow, a couple of months yet. Because when you when you are given a set of rules that work, and you're given the tools and knowledge to test and evaluate those rules for yourself, so you can build confidence in them, then you can start trading. And then you just you start trading one set of rules, then you get another set of rules, and you test and evaluate that. And then you can start trading now, and then the next set and the next set. So you can pretty quickly build a portfolio of strategies, if you're not trying to figure everything out on your own. Right. Grant Okay, so you started to address some of the questions I had for you, which is how long does it take for someone to get proficient using your system? And it sounds like the first part is they could begin some level of proficiency within two months. Is that accurate? Adrian And for both a completely new trader who is motivated and willing to learn and willing to ask questions can be up and running in in with a system in a month or less, then with a portfolio of systems within two to three months. Grant And when you look at that person going after a portfolio, what sort of capital do they need to bring to to this trading style. Adrian So my style is all systematic, and each system is a diversified portfolio of instrumental positions that are hold so what let's say one of my trend following systems in stocks, that makes money as stocks just continue up on their their long trend and then when stocks turn around and go down, it gets out and takes you to cash, that system might hold 20 simultaneous positions. Okay, now, if you're trading the Australian market, the Australian market has this unfortunate rule where each trade has to be $500 in value. You can't place a new trade for $200 It's five Under dollar minimum, so for that system on Australian, you need $10,000 to trade it properly, but in the US not so. And in the Asian markets not so so. So you really, you can start with just a couple $100 Or a couple $1,000 If you choose the right market. And this is one of the reasons why the cryptocurrency market is so great, because you can you can trade a diversified portfolio in the crypto markets with very small positions, and there's no minimums, and the costs are very, very small to trade it. So you really capital isn't really a barrier to entry anymore. It's it's really the learning that is the barrier to entry, you've got to have rules that give you an edge. And you've got to have absolute confidence in those rules. That's what you need to win really. Grant So the biggest challenge that seems over the years in the years that I've been trading as, as the discipline trader mentality, right, the ability to stick with those rules. So what tips or techniques do you have for, for sticking with the rules, right? Not letting the emotions overcome saying, Hey, I'm just going to take the loss, not doing revenge trading, etc. Right? What What are your tips for sticking with the rules? Adrian Yeah, this is this is great, because when I before I, before I became a systematic trader, I was a discretion. I did discretionary technical analysis, and I did fundamental analysis, and I really struggled emotionally. And systematic trading really helped. Because there was no, there's no ambiguity. If you have a system, which is objective that tells you if A and B and C happens you buy if D or E happens you sell, you don't have to wonder, is it a buy signal? Or is it a sell signal? So I think most people will benefit hugely by trading systematically, rather than with discretion. That's the first thing. Second thing is your system won't make money all the time, and it won't be profitable on every trade. It's the the your account is gonna go up and down gradually on a path to building your wealth. So you've got to be comfortable as the account swings around. And the biggest trick to getting comfort is building confidence in the rules. So we have our rules, like I can give you the best trading rules in the world. But if you haven't tested and evaluated them for yourself, then when they start losing money and going into drawdown, it's gonna be really hard for you to keep following them. Right? If you've tested them, and you know, okay, for this set of rules, a 15% drawdown is perfectly normal, or three or five losses in a row was perfectly normal. And if I just keep falling it, I'll come out the other side, if you've done that work, not me telling you that's the case you actually doing the testing, then you can sit comfortably knowing this is perfectly normal. Grant So do you provide the traders with a certain level of back testing tips and techniques to prove that out? Adrian Yes, absolutely. I think this is the the most important thing, because what what most people ask is, what stock should I buy? What crypto token should I buy? The next level of question? It's a very basic question. Next level of evolution is what rules should I follow? Yep. And if someone asks you what rules should you follow? They've evolved beyond keep trying to get tips, right? They're trying to get a process. The Evolution above that is I these are my rules. And I have confidence in them, because I've tested them. And I've evaluated them. So the most important part of my program, my teaching is actually the the back testing, the evaluation, the optimization, improvement of systems, yes, I give systems, but I don't want you to believe and trust me that those systems work. I want to give you the skills and tools to make that decision for yourself. So you can actually follow them in good times and bad. Does that make sense? Grant Oh, total total sense. Yeah. That way that you have a greater probability of being disciplined of sticking with that system and not not bailing when you shouldn't? Or not being able to get back in when you should? That's, that's right. Yeah, yeah. critical aspect for them. So when you think about the portfolio's you've talked about you doing stocks? You doing crypto? Do you do have an approach where you separate the portfolio across those? Or is is crypto always part of it? Or do you just focus in crypto with some of your trading strategies, but different ones in stocks? I know it's a long question. And how do you distinguish between the two trading? Adrian Yeah, it's a good question. It's a good question. And one of the one of the things I realized when I started researching into systems is that different markets move and behave differently. So you know, gold moves differently to oil moves differently to the stock indices moves differently to the Australian stock market. So my rules are developed for each market. Now a great set of rules will probably work on several markets, but you design it for a certain market. So I have rules for the Australian stock market rules for the Hong Kong Stock market rules for the US stock market. And I have rules for the crypto markets and then different. What I have that sits above all of those systems is a capital allocation model. And I say, okay, for my portfolio, I have this X percent in system one y percent in system two, Zed percent in system three, and so on. And each day, when I'm calculating the size for my positions, I go all the way to the top and say, Okay, how much money do I have in my accounts? What are the percentages for each system? And then within each system, how do I size each trade. And by cascading it down like that, you do a couple of things, you make sure you stay diversified, you don't get concentrated, you make sure your risk on each trade is low, and red linked to the amount of capital you've got in that system and in in total in your account. So the systems are all separate, but they essentially trade a common pool of money and have an allocation to each system, which keeps everything safe and balanced. Grant...
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CAIR 63: Using AI To Overcome Labor Shortage !!
02/19/2022
CAIR 63: Using AI To Overcome Labor Shortage !!
In this episode, we take a look at the question Can AI Be Used to Automate the Mundane? Grant Hey, everybody, welcome to another episode of ClickAI Radio. So welcome, I am excited to bring into the show today someone that it's taken me several times trying to get to this, busy busy guy. This is Evan Ryan. Evan, I hope I said your name right, right. Because I've said some people's names wrong. It's not Yvonne right or not right on? Is it Evan Ryan? Right? Evan It is Evan Ryan. Yeah, you got it in the right order. Most of the time, it's in the opposite order to flip it around. Grant Right. Um, founders CEO, King, of Teammate AI, right. Evan I just tried to go by founder. Okay. Grant Awesome. All right. Tell us a bit about yourself, Evan, what's brought you to this point. And anyway, thanks for joining the show. All right. Let me stop talking. Go ahead. Evan Well, Grant, thanks for having me. We were talking before we started recording, I just hit it off from the first second, at least in my opinion, I'm having a wonderful time. So really with me, I didn't really notice this. But throughout my entire childhood, I really had zero tolerance for boring stuff. I was somebody who just really likes doing fun things. And I like doing things that are that are entertaining, that are challenging, that are fascinating, that are motivating. But I don't like doing things that are boring. And I will basically do anything that I can to avoid doing boring stuff. And of course, now Hindsight is 2020. But that's sort of how I view a lot of my childhood. Well, in 2016, I went to a conference where they had this guy by the name of Jeremy Howard. And at the time, or a year or two prior, he was the number one ranked AI researcher in the world. He was talking about all this stuff that you could do with AI. And he, he mentioned that he had this company that could correctly diagnose cancer from MRIs and CT scans. Cool better than a team of board certified doctors. Oh, this isn't 2016. Yeah, so I was just about to graduate from college. I was thinking that oh my gosh, like, this is just the coolest thing I've ever heard. I basically went into AI the next day. Did you really? Wow. Yeah, it was it was really sort of powerful and transformative. Over the next couple of years of sort of iterating around well, what what do I really want to do inside of AI? You know, how do I want to define AI? First of all, there's sort of no definition that everybody can agree upon. I really found that, you know, I hate doing boring stuff. I bet a lot of other people hate doing boring stuff, too. Yeah, yeah. So and so now we all know the pattern there for sure. Yeah. Yeah. And what I've found is really interesting is, you know, one of the biggest conversation topics around AI right now is will AI take all of our jobs? Grant Oh, my goodness. Yeah. I hear that so many times. Yes. Evan I mean, there are like so many ways to answer that with the answer, in my opinion, being No. But what I found is really exciting is when I bring people into the creative process about how can they automate the mundane, the boring, repeatable on their days, they're so excited, like the first time in a while that they felt like, wow, the future is so much bigger than my past. So for the last several years, we've been automating, we've been automating tasks and automating processes for small and medium sized businesses. Grant So let me back up. So you hear this guy speak. You're like AI is the place to go. Your passion is let me take boring out of life. So you're leveraging AI to do that to remove the boring. I remember my dad is really what got me into the, into the technology industry. He was in it if you can believe it, right? So he was like one of the early early pioneers in some of this stuff. And he I remember him using the phrase Boolean shift a lot. He would always talk like, oh, technology is a Boolean shift. And I'm like, What are you talking about? What's a Boolean shift, you know? But this is kind of a Boolean shift with AI something, it's going to totally replace us. But in fact, I think it's a shift to the right, where it starts to automate more and more capabilities. It does require us to re retool. But that's good. Because every big shift, you know, throughout our whole economic history, right, as a country, and as innovation continues to grow, we have to keep shifting to the right terms of the skill sets that are important and critical. So I don't see it as, as this big day AI is gonna come take over, and we're all gonna sit around and become people like on E. What is it Wally, that movie Wally? Right, where they sit around doing nothing? Right, I don't think is that, but I do think it is a shift in terms of the capabilities that will bring and therefore we'll get skilled up in other areas. What are your thoughts on that? Evan Well, I have a question first before, before I answer that, do you have a memory of when you were a child, where you first saw technology, do something and you're like, holy, holy smokes. Grant I do it was that this will highlight the age difference between you and I, it was my, my dad worked in this. So there used to be a competitor to IBM. They're called Control Data Corp, and my dad worked for them. He'd worked on some of the big mainframe systems. And I remember one time, he took me into one of their big mainframe centers, right, and we walk into this room and the fans are running. And the big computers are, and the disk, you know, the tape drive is going, you know, like, just like you see on the old movies, right? And the big disk drives worrying. And my dad sits down and starts coding some things on it. And the computer starts interacting with me saying my name and helped me, you know, asking me questions. And I remember leaning up to and going, this is what I'm gonna do. I don't know everything that just happened there. But I want to be a part of this. So yes, that that was my technology origin story. Yeah. Evan Yeah. For me. So outside of seeing this, like this was years ago, when I was like a small child. I remember my best friend was sending out invitations to a fourth of July, a fourth of July party in the United States. And, and he mailmerge at like age eight, e mail merge, like 500 contacts. Oh, that's everything that is just insane. Like, as incredible as mail merging. And AJ at AJ. Also, like, what is this thing? mailmerge? Oh, my gosh. Yeah, it's so fun to like, kind of think about, you know, there's this like, one time where at some point, you're like, I wonder what else it can do? This is just the beginning. Yeah. But to answer your question, you know, will we will we all end up just kind of like sitting around or being artists all day? I don't think so. The example that I use is, you know, right now you and I are talking over zoom. It took me three clicks in order to get into our zoom meeting. Right? And so what if I went, what if we went back to the 1950s. And we said that in 70 years, you're going to be able to talk to virtually anybody in the world, you'll be able to see their face, the audio quality will be crystal clear. And I'll cost you essentially nothing. But all 1.5 million telephone switchboard, switchboard operators will lose their jobs. Grant Yeah, yeah, it's it's true. Yeah, that Yeah, right. Yeah, no, people like, like, There's no way. Evan Right, and, and so there's always been this sort of technological destruction that has taken place. Even back when we humans created the waterwheel. And now you didn't have as many people moving water to generate power generate electricity, or when we created ladders, and, you know, there are all sorts of different pieces of technology that we've had, over the last several 1000 years that have changed the way that we worked. This is just another one, I think it's a bigger shift than then some of the other ones. But, you know, the printing press did the same thing. There are all sorts of people that were just writing books, they were writing the Bible over and over and over and over again. Well, they lost their job pretty darn fast. Yet we have more people on the planet than ever before, and more people are employed than ever. Grant To do this. I remember one of the startups that I was involved with earlier in my career in Silicon Valley, we're trying to solve the problem of we want to be able to allow software engineers and designers to design systems remotely over the Internet, right. And so in order to do that, we have some some design tools, but we got to make that accessible and you need to be able to manipulate it remotely. Right. This is before there's a lot of big fat network pipes. You know, you know, everyone's got high bandwidth, right. So we were trying to figure out how to get this to work. We ended up getting it to work, but the cost was prohibitive. Right Just so dang grim. So when I think about the progress of technology, it's lots of trying over and over again until you get to this point where enough of the complexity can be abstracted away so that ultimately the end user sees this simplicity enough to say it's adoptable for both ease of use as well as cost perspective. I think we're right there. They I, I think we're doing similar thing, right to go through the same round, which is, can I take some techniques that are advanced that have some value, but you don't have to have massive data science background in order to get the benefits from that, and I see that shift taking place where more and more of it can then become accessible to others? As the cost drops dramatically? Evan I've seen similar things, I I couldn't agree more. You know, I think AI is sort of one of those things that for a decade or two was promised but under delivered, no, yeah. And now it's so it's like it's coming in with a vengeance. And the tools that are being made are super intuitive. The use cases that are being documented, and copied and repeated are ones that affect a lot of people. And I think people are really opening their minds to the idea that they don't have to do things the same way that they always have, just because that's how it's always been done. So I think it's kind of a combination of a huge mindset shift. But also just the tools are flat out better than they've ever been before. And they're finally usable to the point where you can automate things and you can create API's with button clicks instead of with raw code. Grant Yeah, yeah. Which is, which is fascinating. I think it's bringing an order of magnitude capability, and will continue to do that, to the kinds of problems that we can solve it. And it's just, I think, at the crux of it right in others is you look to the future, if you can continue to provide this time to this kind of computational power. And add that in the future to things like quantum, when we start blending both of those, I think the kinds of problems we can solve becomes quite large. But let me pull it back to tell me about the problems you're specifically solving with teammate AI. So So you got into this space, you're looking to go solve some problems with AI, you want to make things simple, what are you making simple? Evan You know, we really love to help entrepreneurial companies, and primarily companies where the executive team really wants to grow, they really would love to grow, they'd love to grow five or 10x, and the next decade or two decades, or even shorter, but they can't bear the idea of doing it while radically increasing their payroll. Right. And the most common complaint that we hear is not you know, I have the wrong team or my team doesn't do great work. It's that my team is underutilized because they have too much stuff on their plate. And so what we really try to automate the problems that we try to solve, are really helping these team members helping these employees identify what are the things that you do in a day that you hate the most, let's not automate the stuff that you love, let's automate the stuff that you hate. And then we'll figure out together how we can automate this so that you never have to deal with it again. And so we do that with with companies, basically, across every industry. The the question, the second question that I get the most often is, what industries does AI work in? And my answer is always well, you know, AI is a little like electricity, like, sure there's the electric company. But every every company was benefited. And every industry was benefited by electricity. And it's kind of a similar thing. Yeah, you know, there's sort of no gift that you can give people that's more valuable than their time, in my opinion. Grant What would be some use cases that you're applying it to? Is it? Is it things like bookkeeping, is it, you know, mundane, you know, administrative tasks? Or is it in other areas that you're applying AI? Evan So every company is a little different? I mean, of course, there's like bookkeeping and accounts receivable, and how can we send invoices out of our ERP smoother or submit website forms for invoicing smoother. But there's also a lot of reporting, sort of data collection, data crunching and then putting that into a human readable format. That way, people aren't in charge of trying to figure out what the data says. Instead, the computer tells you what the most important things are to look for. We use AI to write newspaper articles, write and publish newspaper articles for media outlets across the country. Regardless of your feelings of the media, it costs too much money in order to be able to write an article especially for info journalism, like what happened in the local sporting events. So we're doing that all across the country and all across the world, all the way to multi day processes where maybe We're using machine vision to look at images and see, well, are there any defects in the products that we're working with right now? If there are defects, what are the defects and let's report back to the supplier, let's report it back to whoever's responsible in order to be able to get that quality control, like up to speed and up to where we needed to be. So we do the boring in the mundane like accounts receivable, we also do the really sexy and complex machine vision. And we're reporting back with here. Here's the percentage of products that you shipped us, for example, that that were manufactured properly or are up to spec. Grant That's quite a, that's quite a wide range of use cases. That's, that's amazing. Are you building your machine vision work off of the Open CV material or your you did this all by hand? Evan We use Fast AI's library, which Fast AI was the not for profit that was founded by Jeremy Howard. So basically, Jeremy was telling me in this conference, you know, here's all the great things that you can do about AI, by the way, I have a free and open course. And we found that their library is just absolutely unbelievable. So we'll try as hard as we can to be able to, to be able to build it from scratch. And the reason for that we originally did not try to do that we originally tried to use a lot of the open source. Yeah. But the reason was really interesting. It was that, especially when, when the process that we were automating wasn't related to customer acquisition, lead generation. Yeah, what was happening a lot of times was our was our clients who would get this new capability called this AI that saving, you know, hours or days per week in some cases, and they'd say something to the effect of, you know, everybody else in our industry faces the same problem. Could we license this to everybody else in our industry? Wow. Well, now they had this old legacy business, that they flipped into a software as a service business. And we realized really fast that we that we had to be able to make sure that our solution scaled to more than just one user. Mm hmm. Grant Amazing. So what's been some of the outcomes, you've noticed now that you've been out doing this across a range of companies, what, what's been the impact to them? Evan What's most exciting for me is that all companies are unique, yet all companies are the same. So they all have product delivery, they all have accounting, and bookkeeping, they all have sales and customer acquisition, they all have customer service. And so they all have these sort of functions, that interplay really nicely together. But largely, they're the same. The real differentiator, among a lot of companies is things like their supply chain, their product and their product delivery. So being able to help a wide swath of companies get clarity surrounding, you know, AI isn't just for Silicon Valley. It's not just for Tesla, and Mehta and Apple and Google, right. That's been really exciting. I think that there's a real market shift going on among employees, I think employees really have a smaller and smaller tolerance for doing stuff that's boring and doesn't move the ball forward. And companies are really incentivized right now, to outsource a lot of the work to AI in order to be able to retain their best talent. And so that's been one of the really, really interesting things. I think that's come out of the last six months. Grant Now, I guess I could imagine it would be something like removing them in the mundane so that you can tap into their creative, right, I think that's really sort of what you're after, right? It's try to exploit opportunities to get more creativity from your people. I would imagine in today's market, too, with a lot of attrition taking place and the challenges with hiring, that this also can be beneficial. It's is it part of a play to help people stay in their jobs where you could take some of the mundane out of it, and therefore allow them to do more creative and enjoyable things in their work? Evan It absolutely is. That's actually one of the biggest reasons why a lot of companies decide to work with us right now is because they know that they if it can create a work experience, that's five times better than what it is right now. That key employee might not go looking for an extra $10,000 A year or an extra 20 grand, or for new opportunities just because it doesn't feel like a right fit anymore. And so we're seeing that all the time. We're also seeing on the flip side of it, a lot of companies that are having problems hiring, or they're having problems retaining employees, just overall, maybe they have a 3040 50% attrition rate on new hires in any particular role. They're starting to ask the question, Well, I wonder why. Like, maybe it's us. That's the problem. And it's not them. That's the problem. And so all of those tasks that used to be hired, are now being automated instead. That way they can hire for those more creative and fascinating and motivating roles. I mean, I don't know anybody I don't know anybody who wakes up on a Monday morning looking forward to doing the same stuff they've done for the last five years. Grant Yeah, if they do well, yeah, that's another conversation. But sounds like you use a range of things from RPA to some custom built AI work, you guys have developed is your sort of toolset is that, right? Evan Yeah, whatever it takes to get the job done. A lot of times customers will have specifications. But, you know, Microsoft Power automates a really powerful tool. And there's a lot that you can do with 1000 lines of Python code, right, and with a great AWS or Azure suite. And so we do use, we have a handy and a really kind of wide tool belt. But what we find is that we're using the same tool sort of over and over again, which is really handy, I think, overall, and it makes it so that the tools are getting better over time. Grant They are Yeah, they're definitely getting better. Okay, so for our audience, what would be a call to action for them? If they were wanting to learn more about you and your organization and what you're doing? Evan Yeah, so I think the biggest thing would be head to...
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CAIR 62: Overcome The 4 Pitfalls To AI Ethics !!
01/29/2022
CAIR 62: Overcome The 4 Pitfalls To AI Ethics !!
Grant Welcome everybody. In this episode, we take a look at the four pitfalls to AI ethics and are they solvable? Okay, hey, everybody. Welcome to another episode of ClickAI Radio. So glad to have in the house today Plainsight AI. What a privilege. Elizabeth Spears with us here today. Hi, Elizabeth. Elizabeth Hey, Grant. Thanks for having me back. Grant Thanks for coming back. You know, when we were talking last time, you threw out this wonderful topic around pitfalls around AI ethics. And it's such a common sort of drop phrase, everyone's like, oh, there's ethics issues around AI. Let's, let's shy away from it. Therefore, it's got a problem, right? And I loved how you came back. And it was after our episode, it's like he pulled me aside in the hallway. Metaphorically like "Grant, let's have a topic on the pitfalls around these some of these ethical topics here". So I, you hooked me I was like, Oh, perfect. That's, that's a wonderful idea with that. Elizabeth So typically, I think there's, there's so many sort of high level conversations about ethics and AI, but, but I feel like we don't dig into the details very often of kind of when that happens, and how to deal with it. And like you said, it's kind of the common pitfalls. Grant It is. And, you know, it's interesting is the, in the AI world in particular, it seems like so many of the ethical arguments come up around the image, style of AI, right, you know, ways in which people have misused or abused AI, right for either bad use cases or other sort of secret or bad approaches. So this is like you are the perfect person to talk about this and, and cast the dagger in the heart of some of these mythical ethical things, or maybe not right. All right. Oh, yeah. Alright, so let's talk through some of these. So common pitfalls. So there were four areas that you and I sort of bantered about, he came back he said, Okay, let's talk about bias. Let's talk about inaccuracy in models, a bit about fraud, and then perhaps something around legal or ethical consent violations. Those were four that we started with, we don't have to stay on those. But let's tee up bias. Let's talk about ethical problems around bias. All right. Elizabeth So I mean, there's really there's several types of bias. And, and often the biased and inaccuracies can kind of conflate because they can sort of cause each other. But we have I have some examples of of both. And then again, somewhere, some where it's it's really biased and inaccuracies that are happening. But one example or one type is not modeling your problem correctly, and in particular, to simply so I'll start with the example. So you want to detect safety in a crosswalk, right, relatively simple kind of thing. And, and you want to make sure that no one is sitting in this crosswalk. Because that would be now generally be a problem. It's a problem. So, so you do body pose detection, right? And if you aren't thinking about this problem holistically, you say, All right, I'm going to do sitting versus standing. Now the problem with that is what about a person in a wheelchair? So then you would be detecting kind of a perceived problem because you think someone sitting in the middle of a crosswalk but but it's really just about accurately defining that problem. And then and then making sure that's reflected in your labeling process. And and that kind of flows. into another whole set of problems, which is when your test data and your kind of labeling process are a mismatch with your production environment. So one of the things that we really encourage for our customers is, is collecting as much production close as close to possible, or ideally just production data that you'll be running your models on, instead of having sort of these very different test data sets that then you'll then you'll kind of deploy into production. And there can be these mismatches. And sometimes that's a really difficult thing to accomplish. Grant Yeah, so I was gonna ask you on that, you know, in the world of generative AI, where that's becoming more and more of a thing, and in the app, the appetite for sort of generating or producing that test data is the premise that because I've heard some argue, wait, generative AI actually helps me to overcome and avoid some of the bias issues, but it sounds like you might be proposing just the opposite. Elizabeth It actually works both ways. So um, so creating synthetic data can really help when you want to avoid data bias, and you don't have enough production data to, to do that well. And so you can do, you can, you can do that in a number of different ways. data augmentation is one way so taking your original data and say, flipping it, or changing the colors in it, etc. So taking an original dataset and trying to make it more diverse and kind of cover more cases than you maybe would originally to make your model more robust. Another another kind of way of doing that is synthetic data creation. So an example there would be, you have a 3d environment, in one of these, you know, game engine type things like Unreal or blender, you know, there's, there's a few, and you have, say, I want to detect something, and it's usually in a residential setting, right. So you can have a whole environment of different, you know, housing types, and it would be really hard to get that data, you know, without having generated it, right, because you don't have cameras in everybody's houses, right. So in those cases, what we encourage is, pilots, so you before, really, you know, deploying this thing, and, and letting it free in the world, you you use that synthetic data, but then you make sure that you're piloting that in your set in your real world setting as long as possible to, you know, sets out any issues that you might come across. Grant So let's go back to that first example you shared where you got the crosswalk, you have the pedestrians, and now you need to make sure you've got different poses, like you said, someone you know, sitting down on the road or laying on the rug, certainly using generative AI to create different postures of those. But But what about, hey, if the introduction, is something brand new, such as, like you said, the wheelchair or some other sort of foreign object? Is the generative AI going to help you solve for that? Or do you need to you need to lead lead it a bit? Elizabeth It absolutely can. Right? So yeah, it's, it's basically anything that you can model in a 3d environment. And so you can definitely model someone in a wheelchair in a 3d environment. And, and Tesla uses this method really often because it's hard to simulate every kind of crash scenario, right? I mean, sorry, it's hard to have real data from every kind of crash scenario. And so they're trying to model again, they're trying to model their problem as robustly as possible. And so in some of those cases, they are like, you know, all of these types of things could happen, let's get more data around that the most efficient, and kind of most possible way of doing that is with synthetic data. Grant Awesome. Awesome. Okay. So that's a key approach for addressing the this bias problem. Are there any other techniques besides this generative, you know, training data approach? What else could you use to overcome the bias? Elizabeth Yeah, so. So another type kind of is when you have, like I was saying a mismatch in test and production data. So a lot of people even you know, computer vision, people sometimes don't know how much this matters. When it's things like, for example, working with a live video. So in those cases, bitrate matters, FPS matters, your resizing algorithm and your image encoding. And so you'll have, in many cases, you're collecting data in the first place for your test data differently than it's going to run in production. And people can forget about that. And so this is a place where, you know, having a platform like plain sight, can really help because that process is standardized, right? So the way you're pulling in that data, that is the same data that you're labeling, and it's the same data that you're, then you know, inferencing on, because you're pulling live data from those cameras, and it's all it's all managed in one place and to end. So that's, that's another strategy. And another thing that happens is when there are researchers that will be working on a model for like, two years, right, and they have this corpus of test data, but something happens in the meantime, right? So it's like, phone imaging has advanced in those in that time, so then your your input is a little different, or like the factory that they were trying to model, the the floor layout changed, right. And they didn't totally realize that the model had somewhat memorized that floor layout. And so you'll get these problems where you have this, you know, what you think is a really robust model, you drop it into production, and you don't know you have a problem until you drop it into production. So that's another reason that we really emphasize having pilots, and then also having a lot of different perspectives on vetting those pilots, right. So you, ideally, you can find a subject matter expert in the area outside of your company to, you know, take take a look at your data and what's coming out of it. And you have kind of a group of people really thinking deeply about, you know, the consistency of your data, how you're modeling your problem, and making sure that kind of all of those, all of those things are covered? Grant Well, in reducing cycle time from this initial set of training, to, to sort of validation of that pilot is crucial to this because as you're pointing out, even even if you even if you keep that cycle time short, and you do lots of iterations on it, some assumptions may change. How do you help? How to me what's the techniques for, you know, keeping someone looking at those assumptions? Like you said, maybe it's a change in camera phone technology, or it's a change of the layout? Like I said, as technology people, Einsteins we get so focused on oh, we're just pushing towards the solution, we sort of forget that part. How do you how do you get someone? Is that just a cultural thing? Is it a AI engineering thing, that someone's got a, you know, a role in the process? To do that? Elizabeth I think it's both. So I think the first thing is organizations really need to think deeply about their process for computer vision and AI. Right. And, and some of the things that I've already mentioned, need to be part of that process, right? So you want to research your users in advance, or your use cases in advance and try to think through that full Problem Set holistically. You want to you want to be really, really clear about your labeling, right? So you can introduce bias, just through your labeling process if humans themselves are introducing it, right? Exactly. If you have some people labeling something a little bit differently than other people. So like on the edge of an image, if you have a person on the edge, do you count that as a person? Or is it or you know, or as another person? Or is it not counted? How far in the view do they have to be? So there's, there's all a lot of gray area where you really just need to be very familiar with your data. And, and be really clear, as a company on how you're going to process that. Grant So this labeling boundaries, but then backing up, there's the label ontology or taxonomy itself, right, which is, yeah, that itself could just be introducing bias also, right. Elizabeth Yeah. And then back to kind of what we're saying about how to ensure how to really think through some of these problems, is you can also make sure that that as a as a company, you have a process where you, you have multi passes, multiple passes on, on that annotated data, and then multiple passes on the actual inference data, right. So you have a process where you're really checking. Another thing that we've talked about internally, recently is you know, we have a pipeline for deploying your computer vision. And one of the things that can be really, really important in a lot of these cases is making sure that there is a human in the loop that there is some human supervision. To make sure that you're, you're, again, you weren't servicing bias that you didn't under your you didn't anticipate, or your your model hasn't drifted over time, things like that. And so something we've considered is being able to kick off just in that process, have it built in that you can kick off a human, like a task for a person, right? So it's, it's just built in. Grant And so it no matter what you do that thing is this, it's just as a governance function, is that what you're getting? Elizabeth Kind of so it's like, it's like a processing pipeline for your data. And, and so you can have things like, Alright, at this step, I'm gonna augment my data, and at this step, I'm gonna, you know, run an inference on it, or flip it or whatever it is, right? And so, in that you could make sure that you kick off a task for a human to check, right, or, or whatever the case may be. Yep. Yep. So there's several good, so good process maturity, is another technique for how do we help overcome bias as well as inaccurate models? And I'm assuming you're, you're almost bundling both of those into that right? In Yeah, both right. And, and like you said, they're the another way is reducing that time, and also making sure that you're working on production data whenever possible. So reducing the this, this is where the platform can help as well. Because when you you know, you aren't off in research land, without production data for two years, but you have a system where it makes it really easy to connect cameras, and just work on on real production data, then two things, you're, you're reducing the time that it takes to kind of go full circle on on labeling and training and testing. And then also you you have it all in one place. And that's that's one of the problems that we solve, right? Because, in many cases, computer vision engineers or, or data scientists, they're kind of working on the they don't have the full pipeline to work on the problem. So they have this test dataset, and they're working on it somewhat separately from where it will be deployed in production. And so we try to join those two things. Grant Yeah, I think that's one of the real strengths of the platform of your platform, the plain side platform is this reduction of the cycle, so that I can actually be testing and validating against production scenarios, and then take that feedback. And then augmenting that with the great governance processes you talked about. Both of those are critical. Let's let's talk a little bit and talk about fraud is, you know, certainly in this in computer vision, holy smokes, fraud has been probably one of the key areas that, you know, the bad guys have gone after, right? All right, what what can you do to overcome this and deal with this? Elizabeth You know, it can really become a cat and mouse game. And I think the conversation about fraud boils down to, it's not clear, it boils down to is it better than the alternative? Right? So it's not clear that just because there could be some fraud in the computer vision solution, it may or may not be true that there could be more fraud and another solution, right. So so the example is, technically, you used to be able to and I think with some phones, you still can 3d print a face to defraud your facial detection to unlock your phone. Yeah. And there is and so then they've, you know, done a lot of things, advancements, so this is harder to do, which, like there's a liveliness detector, I think they use their eyes, your eyes for that. And then you know, there's a few but you could still use a mask. So again, it's it's this cat and mouse game. And another place is is you know, there are models that can understand text to speech. And then there are models that you can put on top of that, that can make that speech sound like other voices, right? So the the big category here is deep fakes. But it's, you know, you can you can make your voice sound like someone else's voice. And there are banks and other things like that, that use voice as a as a method for authentication. Right, right. Grant I'm sure I'm sure we've all seen the the Google duplex demo or scenarios right. says a few years from now, right? I mean, that technology obviously continues to mature. Elizabeth Exactly. And so, so then the question is Okay, if I can 3d print a face and or a mask and unlock someone's phone, is that is that is that harder than actually someone just finding my, you know, four to six digit phone, you know, numerical code to unlock my phone. So, you know, so I think there it really becomes a balance of which thing is is harder to defraud and in fraud in general, you know, if you think about cybersecurity, and, and everywhere that you're trying to combat this, it's a it's a cat and mouse game, right? People are getting, you know, people are figure out the vulnerabilities in what exists and then and then people have to get better at defending it. So well. So the argument is, if I if I can say back to the argument is, yeah, it exists. But hey, how's this different from so many other technologies or techniques, where again, you got fraudsters trying to break in? This is just part of the business today? Right. That's where it is? Grant Yeah, I think it becomes a, an evaluation of is it? Does it cause more or less of a fraud problem? And then it's, it's really just about evaluating the use of technology on an even plane? Right. So it's not it's not about should you use AI? Because it causes fraud? It's should you use any particular method or technology because there's a fraud issue and what's gonna cause the least fraud? Right, a more specific use case? Elizabeth Yeah. Grant Yep. Okay, so So fraud. So, uh, you and I had talked about some potential techniques out there. Like there's a Facebook Instagram technology algorithm. Right. I think it's called seer. I think it came out not too long ago. It's a it's an ultra large vision model. It takes in more than a billion variables. P believe that. That's, that's a lot. A lot of massive. I mean, I've built some AI models, but not with a billion. That's incredible. So are you familiar with that? Have you looked into that at all SEER itself? Elizabeth Yeah, so So this, basically, this method where you can look, basically to try to address bias through distorting of images? Yeah, yeah. So I can give you a good example of something that actually we've worked on, I'm going to chase change the case a little bit to kind of anonymize it. But so in a lab setting, we were working on some special imaging to detect whether there was a bacteria in, in in samples, or not, right. And in this case, we were collecting samples from many labs across the country. And one thing that could be different in them was the color of kind of the substrate that the sample was just in, it was essentially a preservative. Wow. And so but but those, there are a few different colors. And they were used kind of widely. And so it wasn't generally thought that, you know, this would be a problem. But so the model was built and all the data was processed. And there was a really high accuracy. But what happened, and what they found out was that the, there was a correlation with the color and whether the bacteria was present or not. And it was just a kind of a chance correlation, right. But if you had had something like that, that image distortion, so if you took the color out automatically, or you mess with the color, then that would have taken that bias out of that model. And then as a second thing happened, actually, which was when the, the the people in the lab, were taking the samples out of the freezer, they would take all of them at once. And they were just kind of bordered. And so they...
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CAIR 61: AI Signal - The Fastest Route To Gold
01/22/2022
CAIR 61: AI Signal - The Fastest Route To Gold
In this episode, we take a look at how to get AI signal on your business. Hi Everybody, welcome to another episode of ClickAI Radio. So you are busy running your business, right? And of course, you often wonder, is there any way for me to work smarter, not just harder? Well, years ago, and one of my startups I was working 100 hour workweeks absolutely crazy. And I was trying to keep everything moving for right, we had a very challenging client, that really took up 80% of our energy and the other 20% of the energy was spent on other clients, as well as all the administrative things right that it takes to run a business. One night, while we were writing and testing a bunch of code. I looked at my teammates and exclaimed, ah, there's got to be a better way. And they agreed. So we decided to step back and we looked at the assumptions on which we're operating. Number one, could we adjust the clients expectations, and number two, perhaps we could look at all the information at our disposal and look for insights, things that we weren't seeing. So we did both of those. And of course, at the time, we did not have AI, but we perform something that you might call AI signal. So the takeaway from the story is that by addressing both of those items, of course, we dramatically improve the outcome of the business. Number one, with regards to adjusting the expectations. This was, of course, one of those common sense functions. That should have been done months earlier. And of course, I'll chalk that one up as a life lesson. But number two, looking at our data and searching for insights, we found some clues that told us how to improve. So what is AI signal? Well, it's, it's similar to tipping your toe in the water before fully committing. Alright, so that reminds me of a backpacking story. When our kids were younger, we were backpacking, in the flat tops wilderness area of Colorado, and it was still early in the summer. And so there's plenty of snowpack melt, you know, coming down through the streams, and, you know, AI signal, we had to cross the stream, right, we couldn't find a way across, it was much too wide to jump. But we knew we had to get in and get over to the other side. So AI signal would be similar to testing the temperature of this fast moving water before hopping in, as well as getting a sense of how deep the stream is, and how fast the water is moving. Well. Did we do any of that? No. And so you know, we would have saved ourselves some emotional as well as physical heartache, if we would have tested out the conditions first. So instead, we took a run at it and jumped as far as possible, right. Meanwhile, the fast and very cold moving stream just switched, you know, with this downstream, right. So don't do it that way, obviously. Now, this, of course, applies to your business. And especially when it comes to AI, get some AI signal first on your business data to put your toe in the water. So let's look at an example. Imagine, imagine you have one or more systems as part of running your business, it might be a CRM, with sales data, you also might have a lead management system. And now they may or may not be connected to each other, when in fact, let's say they're not connected. Now, you only have so much time, obviously, and resources each week as a business owner. And so the question is, how can you improve the use of your scarce commodity of time each week? Well, one way to help you do this to fine tune quickly is to look for a signal. Well, what does this look like? Well, lets you know when you do an AI project. If you don't use a turnkey provider, like ClickAI, then you're gonna do the work of cleaning up the data and getting it ready for AI. This is is and can be a really significant effort on your part. And it interrupts Of course, all of your other business operations. But what if you could find out if there's enough predictive behavior in your data before you even spent the time to clean it up? So this is what AI signal is, right? It's an AI technique to preview your not so prepared data and run enough AI on it to determine if there's some signal in it that could ultimately be used to one, improve your efficiencies and to grow your sales. Now, in the example that I gave above, you know, you may decide to look for signal in your lead management data. And separately, you may decide to look for signal in your CRM data. But if there's enough signal in the data in one or both of those systems, you may want to knit those together, or have a turnkey provider and that those together for you. So for example, if your CRM CRM system has a history of sales and refunds and things like that, imagine the value of connecting your leads data to your sales data, of course, so you could see through the AI, things which could translate leads into either sales or refunds, you really want to know both right? The kinds of leads that is going to ultimately translate into refunds, the ones to ignore now, of course, it all starts with just getting AI signal. That's a, it's a powerful first step that lets you know if your data has AI potential, and if so, which data elements are the biggest contributors, that's incredibly powerful. This is, this is better than taking your car to the mechanic shop where the signal may be spend more money in these areas. It's more like having a gold mine and the mining engineer stating, hey, in this part of the mind is a vein of gold. And over here in this other cavern, there's another vein of gold. Alright, now you know where to focus and where to dig. So once you've course commenced with mining the material, but the real question is, what do you do with the material meaning with the goal meaning with the insights you receive? Well, getting an AI signal is exciting, of course. And it's dramatically time saving, it'll save you a ton of time just to know where the gold is. But getting the AI gold is even more exciting, and even more impactful now, using the quote unquote AI gold to grow your business and of course, improve the value of your business opens a lot of doors. All right, everybody. Thanks again for joining. Until next time. Check your business for AI signal. It's the fastest route to business value. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com now.
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CAIR 60: Use Tech Half-Life To Grow Your Business !!
01/18/2022
CAIR 60: Use Tech Half-Life To Grow Your Business !!
Hey in this episode we take a look at how you can use the technology half-life to build your business. Everybody, welcome to another episode of click AI radio. So thinking about half life, technology half life, what does that mean your business? And how quickly are things changing? It's interesting in terms of the you know, different organizations have different views on how fast things are changing sort of the, the sort of the pop culture, if you will, of technology tends to treat it like things are changing quickly. And that and that that certainly feels that way for lots of us. It's interesting, though, to see the different viewpoints on it. Let's let's take a quick look at this. So here's one and that this comes from culture.io. Right, they talked about how digital transformation is more successful with a positive shift in culture, in fact, goes on to say 80% of enterprises will change their culture as a way to accelerate their digital transformation strategy. That's actually a Gartner statement. So the point here is that, hey, if if you are if technology is changing a lot, and it's, you know, impacting your business, you better change your culture. Alright, let's check off the box for the culture statement. Let's move on from here. So how fast is technology changing? Or what pace or rate are things changing? Singularity hub.com has got this interesting viewpoint where they they show the growth in the DNA sequence data over years, right, where they show the Internet backbone bandwidth over you know, over the years, all of these are course up and to the right in terms of you know, what we see on the graph, right? Or the number of bits per second, you know, over the years, right, or the number of bits per second per dollar, right? So you end up getting more and more, more and more data for your dollar. Alright, so these logarithmic charts come from Ray Kurzweil Neil's 2005 book, The Singularity Is Near right, and it's attempting to show that certain things are growing exponentially. All right. However, there's other views. This comes from itI, f.org. They've gotten an opposing view, they're they're making comments like, Well, wait a minute, is a really changing that quick. They make this comment, they say, Look, if technological change actually were speeding up, one would expect to see an increase in patents and productivity, but we don't. All right, they also go on to say from 2006 to 2015, US utility patents increased just 3.8% per year. And then they go on to talk about productivity, growth, so the productivity improvements of labor. So from 1980, in the US productivity, annual annual productivity growth in US was about 1.5% 1995 was up 2.5%. And, and from 2007, and 2017. It was only 1%, which is interesting, showing that the actual productivity, even though all these new technological wizardry, cool things are around us, as our productivity actually increasing. Well, they go on to make this interesting comment. I'm just going to read this right here. They make this point right here, they say, look, many technologies today are nowhere near half patent or penetrating half of the American homes a decade after they first commercialized. So they go on to point out that Fitbits came out in 2007. You know, consumer 3d printers in 2010, VR 3d goggles, 2015, none of them are anywhere near 50% market penetration. So the question is, well, so Alright, maybe maybe there's this increase of many new different types of technologies, but in terms of their adoption, and the impact in our lives and making us more productive. These guys are arguing that it's not really making a difference there. What is changing or growing fast, and this comes according to hosting tribunals. dot com, they have an interesting set of stats, he pointed out that what is growing is things like, like the number of smart devices, right? As well as the number of hosting services and, and and the number of websites, right and the amount of data and those are things that all tend to be increasing and growing, what up to almost 2 billion websites now. But some say that, that can only 75% of those websites aren't active. And so while there's still a lot of stuff out there and a lot of data growing, the real question is, is it making us more productive? And is it doing more for us and helping us to become better? What we are getting is a lot more data. So here's something from MIT, MIT said, Look, when it comes to changes, right, in terms of the amount of changes that are taking place, from their perspective, they felt like it's varies based on the industry. So it says from a low 2% per year for the mechanical skin can you know skin hair treatment, skin treatment, hair removal wrinkles, to a high of 216% per year for the dynamic information exchange and support systems. Their point is this. The rate of change from 2% to 216% varies across different industry. So one industry might see tons of new technologies, new changes, whereas the other hardly sees anything changing or it's changing very slowly. And even if things are changing, are they really making things better? Well, here's one of the challenges. With the increase in terms of numbers of technologies and things that are out there again, things have to be adopted to really make a difference. The one thing that folks are seeing is that there's a half life, that's taking place, there's a half life of the technology because of the numbers of things that are changing. So in general, we see that their half life is going down. And the other thing that's that's happening in terms of Half Life is around the skills of the people. And so this comes from emeritus.org blog, there talks about the half life of employee skills. I'm just going to quote here, World Economic Forum research in 2017, said that the half life of a skill is about five years, that was in 2017. And then by the end of 2021, was estimated to be down to four years now that those were just employee skills in general, some feel that the that that number is lower for technology skills, I've seen some folks say it's down to even three years. So if the half life of your technology skills, let's say that it is around three years, so you spend your time as an organization, you you're investing in the technological skills, so you're going to use technology to help compete, but the half life is, let's say three years for that. What that means is of course got to keep keep ahead of that curve. And as a small to medium business owner that starts to become fairly expensive value proposition. Here's, here's another piece right here, it says of the existing 25 million software developers 50% will witness the half life phenomenon to their skills. So means that without additional upskilling, only about 12 point 5 million of them are going to be suitable for jobs that we need to have them do by 2025. So that's a shortfall of about 18 point 5 million jobs. Alright, let me say it another way. So you're small to medium business owner, you're trying to use technology to be competitive, but the half life of technology is reducing whether or not it's making you more productive. That's another argument, as well as the half life of the skills of the people to bring the technology down to three to four years, that starts to become really expensive. So while it can be argued that the technological pace of change varies in different industries, it can also be argued that access to the skilled teams to leverage AI for your business is like fighting a drying or fight fighting around a drying waterhole in the Sahara Desert, right? It means that, you know, less and less water, you know, everyone's fighting for the last little bits or drops of it. As an SMB owner, though, I'm going to suggest that it's critical to not play the game of building your AI technology team using your scarce resources. So what I am suggesting, though, is that with the advent of democratized AI, and there's a bunch of platforms out there, like with ClickAI and able with Plainsight AI, who I've had them on here, before, you know you should take advantage of these platforms. And the benefit is that you abstracting the AI complexities away from you, while delivering the benefits and the values that AI has to offer. So the argument is this, given the democratization of AI that's available given the half life of skills for the people and the half life of technology itself, why would you do or take another approach without using democratized AI? So as always start with your business use cases and then of course, leverage democratize AI rather than investing in technologies with with you know, such a short to HalfLife Alright everybody, thanks for joining and until next time, spend your half life wisely. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com, now.
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CAIR 59: Hey AI, Where Are MY RESULTS??
01/03/2022
CAIR 59: Hey AI, Where Are MY RESULTS??
Hey, AI where are my results? In this episode, we take a look at some of the fundamental principles to getting results for your business using AI. Hey, this is Grant, Welcome to another episode of ClickAI Radio. All right, so I've been thinking about this issue around AI and the ability or inability of businesses to get the results from their AI efforts. So I'm gonna quote here again from Bernard Maher's book, it's called artificial intelligence in practice, he actually points out some interesting, he's got a series of use cases, or case studies, I should say, with their various use cases where AI has been applied, and what some of the outcomes or the results of those arms is going to pull from one of these here, this was a Kimberly Clark experience, where they were looking to produce some, some AI insights based on their customer data. Alright, so customer segmentation problem, how do we go after the market and try to improve our targeting with our marketing efforts and use AI to understand where to go with that. So what they did was, as they applied the AI, they ended up increasing their signup rates by 17%. And then they ran some other campaigns to optimize targeting of customers, this was for their dipende brand, and they saw a 24% increase in conversions. So how did they do that? Well, they they did it mostly by producing content, that more closely aligned with the customer profiles, that the AI predicted would be more responsive. So there's a great a great use case here, right in terms of applying AI to to this sort of marketing problem and customer segmentation area. Now, these customers, what they also found, was it, they ended up becoming more likely to be long term repeat buyers. So it's one thing to have an increase in conversions and sales, but to turn them into longer term buyers. That's a real bonus. Certainly, it also had the had the downstream effect of making them more likely to give positive recommendations to friends and family. So this is a great example of of successes for AI, right, it's a great use case for where we would apply it, and the kinds of sort of long term benefits that we want from AI. Of course, what we're finding is more and more market leading companies are transitioning into tech companies. And if we're not thinking of becoming a tech company, it actually is continues to move to our disadvantage. So it's essential that we do that, of course, we want to be competitive and, and even stay ahead of the pack, if you will. But turns out that AI driven Analytics is a lot more powerful than the you know, traditional business intelligence solutions are out there previously, and still certainly in use today by a lot of organizations that are focusing a course on customer segmentation. But the real point is, by applying AI ultimately into the space of doing custom customer segmentation, the AI is able to see things of course that difficult for our brains to get get get wrapped around. But it's also has another impact that we're seeing, and that is that the businesses that are competing, of course, as our businesses each compete in the pool and the talent pool and the challenges we face at this time of year not producing this at the beginning of 2022 when we've got a lot of not only supply chain challenges, but resourcing problems and a lot of competition for talent in our businesses. You know, building our business in tech savvy ways and leveraging the the technologies such as AI, of course to help us to be more competitive. Those also tend to attract a certain type of talent to our to our companies also. So it's a it's important part of building our representation, a reputation and our branding. But I want to talk about But the other side of it, right, so that sounds like you know, roses and apple pie and motherhood and so forth, right? Everything's great. Turns out, of course, as we all know, AI has had its failures. But I found that particularly interesting view of this from the I triple e.org site, they were describing some AI failures. And it's interesting, as you look at the different set of failures, typically, it's it seems to be a lot in some of these areas where, where there's, you know, AI is being used in these use cases that are, you know, pushing the edge and the envelope, which, of course, is what we should be doing for our r&d. But you know, when I think about AI, my focus is more on how can I apply it to benefit my business, right, to improve my customer service to increase my revenues, my profitability, my efficiencies, and so forth? Well, it turns out that a lot of these are fairly r&d centric, use cases, that IEEE sort of points out not surprising, given that it's IEEE but I'm just gonna point out some of these right, and then and then take, hopefully point out some takeaways. Number one was brittleness, they felt like AI is quite brittle, especially this was in a computer visioning use case. And that as as the as the world of the imaging kept changing, then they had to do a lot of a lot of AI rework so so brittleness of AI models, in some use cases, that's That's true statement. So is that a failure? Well, it might be, I guess, right, depending on your use case, number two, the embedded bias problem, I touched on that earlier, especially when I was having a conversation recently with a couple of the organizations that I've done some interviews with, so I'm not going to drill more on to that. This is something that we have to be mindful of, as we're building our AI models to help our businesses. Number three, catastrophic forgetting, that's an interesting phrase right there catastrophic for getting in here, they point out the double deep fake problem, right. And, and here, they're discussing how, you know, bad actors in the market, who are doing this deep fake work. And, you know, organizations trying to compete against that the constant retraining of AI models to include not only new deep fake techniques, but also the need to deal with previous and older styles of deep fake. This certainly is critical. Is it a failure? I don't know, I kind of look at that as the cost of doing business conceptually, right? That if we're in that world, where we got to keep figuring out which we do, how to address this deep fake problem. But nevertheless, AI models are, you know, if you don't include the data in your retrained model, then yes, it can, quote unquote, forget old stuff. So it's not like our cognitive brains were well, I guess depends how old you are. Then you don't forget things as humans, right. Okay, number four explainability. This is a challenge with AI. And in particular, it's a challenge as it relates to giving X explanations for results. And predictions can sometimes be be difficult to do, right, where there's some of these questions. And predictions that come out are hard to to explain how it is that this was arrived at. And as a result, I'm going to give a suggestion on this here in a moment to help address some of this stuff. I think explainability is a real challenge for so is it a failure? It's it's it's a challenge for sure. Number five Quantifying uncertainty. So hey, here we go. Once again, having sufficient data sets that deal with fringe or edge use cases is critical. This is a, I guess, maybe a failure in the sense that sometimes as humans, we don't do that. And we focus on the Happy Day scenarios. But turns out, our brains and real life have to constantly be dealing with all the other fringe cases as well. So it does put the onus on us as business owners to make sure that we're collecting as wide a set of data as possible. And that not necessarily means more and more data means more coverage of you know, the different use cases of data out there that we have number six common sense this was a failure, the I triple C I triple E was pointing out common sense meaning turns out AI lacks common sense. Sometimes us as humans lack common sense in any event, the ability, of course, to reach some logical, acceptable conclusions, right based on our, you know, vast understanding and context of everyday knowledge. You know, a lot of times we take that for granted and well AI doesn't really have that at least in our current current maturity levels of AI, we just don't have that. as such. I think one of the things that I've seen and how I tend to view it as I work with organizations is this AI stuff really should be looked at as augmented intelligence. So the bottom line is, Do not throw your brain away, right this stuff is, is AI stuff in our Yes, we should look at it as it's going to be bringing insights Bhutia, challenge it, right. And so when it comes into us with some insights, we should look at in terms of the realm of possibility, as well, turns out one more number seven terms of failures, what I triple E was pointing out was math. He said, Well, look, you know, simple number crunching tends not to be handled so well with AI. So in addition to not throwing your brain away, don't throw away your old calculator, right? Or, of course, all of your old, you know, sequential linear software, right? That's doing real stuff today, running your business in the economy and such. So AI's got its place, and these seven, quote unquote, failure areas, I think, have that I think there's some some techniques that we can use to get around some of it. Not all of it, but some of it, but what it does is it pushes us into a set of use cases, where, excuse me, we can still get AI value. So to get the best insights from your AI, I think the net net is somewhere in this area, a letter A, I decided not to do a number one, letter A define your Chris questioning, right, which drives focused AI model preparation. So it means we got to think we got to think about the business and not about the technology. As we're as we're organizing, what we're going to go do with AI that has has to happen. Be not number two, but be I guess, here we go be. So when it comes to data, be prepared to continually add to your data set and rebuild your models, this notion that you know, build it once and it's done kind of thing that that needs to go away. And then see, use AI like an augmented intelligence tool, as I pointed out earlier, right? So use an AI platform as part of this that can take your feedback to influence the AI model. You are the brains. Alright, and so as you're getting some insight or predictions on things to do, be sure to come back and inform what was the impact of that was a positive? Was it negative that do what we expected? We need the AI models to continue to be informed and learn from this. Alright, so AI does a great job identifying insights on correlations, of course that are difficult for our brains to see, but we should review it as business owners within the context of our business. Right, we got to keep that in mind and evaluate the veracity of applying that insight to our business. I had to get the veracity word in there just shouted intelligent earlier look at the very the can we actually take this insight and apply to our business? Right? That's really what we're after, not just to have the, you know, the aha moment. Oh, that's great insight. But hey, can I make some concrete adjustments, it's going to change my business and actually bring some bring some benefits about so a I want its approach approached right, using the techniques that I mentioned above my experiences, it really can't help our business. But the industry is also gathering context on the failure scenarios. And so of course, we're going to be best served if we take that into consideration, no doubt about that. So I was looking at something else here. medium.com, you can find some interesting blog, articles and such out there. It pointed out, okay, let's say that, is there a single point of failure for AI. And I found this to be an interesting point that was made here on this particular piece here. Is there a single point of failure for AI and there was this blog on medium.com. That suggests there is and as I reviewed it, I thought, Hmm, interesting. So this piece suggests that to get started with AI, you should not choose a company wide AI implementation, but rather a proof of concept that gets the company accustomed to the new normal, right in my experience, the new normal includes the following activities. These are going to sound like the ABC items I just mentioned. I'm going to use 123. Now just switch it up number one, alright, the new normal if you're going to go apply AI Think about doing these things. Number one clarity in the questions, the business questions or seeking from the AI. Sound familiar? Number two, data curation doesn't have to be perfect, but you got to have for thought and organization on your data. And of course, its potential relevance to the questions you're asking. And number three, a mindset of iterative AI model refinement over time. Alright, so I think I've said those three things several ways in this episode. All right, so let's get to the point of this particular piece here. Is there a single reason for AI project failure? And you hear all sorts of stats out there, right? Maybe half of the projects fail? Or some say 85% of the projects fail? Is there a golden thread? According to this particular bar, blog, or article? They stay? They say, yes. And the answer is expectation management. Right? So organizations have of course, said amazing things to me about what they expect from their AI. This has to be managed early in the process. So I agree with the sentiment, right? It's certainly not as quantifiable, right? It's not to say, Oh, the, you know, common point of failure is you didn't have clean data or enough data or whatever. Certainly, the best practices are we got to have that data and etc, etc. But expectation management is really an interesting point on that. And I agree with that. As I've reviewed this thought about this right, I've developed a guide for smart steps to business outcomes with AI. If you're interested in that, reach out to me click ai radio.com Just join my email list. I'll make sure you get get that to you. Hey, everyone, thanks for joining and until next time, then edge manage manage your AI expectations to achieve the results which are there to benefit your business using AI. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com now.
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CAIR 58: The Data Privacy 2-STEP For YOUR AI
12/31/2021
CAIR 58: The Data Privacy 2-STEP For YOUR AI
In this episode, we take a look at some simple steps to protect the privacy of the data for your AI. Welcome everybody to another episode of click AI radio. Well, certainly data privacy has been on the minds of a lot of people and organizations and governments and governments and institutions, and so forth. No surprise there. One of the things though about AI is that, in general, it's not spent as much time if you will, putting a focus on that area. And it's been a bit of a problem and will become more of a problem if we don't do something about it. As we work with our application and use of AI itself. Now I was looking at several different groups and what they talked about and what they felt about it. At the end of this episode, I'm going to throw out two steps that I have seen that help us mitigate the challenges around this right to help to prevent some of the challenges of slippage, if you will, of getting the privacy of people's information out there that that shouldn't be now to frame that up. I want to introduce a framework for it. One of the one of the blogs, I looked at those, it was called beware the privacy violations and artificial intelligence applications it came from comes from is a see if I can say that is aca.org. There you go. A blog from there. Anyway, here, I'm gonna read an interesting quote here, right said, Look, artificial intelligence has been no different when seen through a privacy by lens design lens, as privacy has not been top of mind in the development of AI technologies. Yeah. All right. So end quote there. I agree with that that has been true. In fact, a lot of our efforts have been, can we just prove the viability of this technology in terms of helping people, individuals, businesses, certainly, there's been success with AI. And there's been some challenges. Now, they what what's introduced here is three interesting pieces to consider. When we're looking at privacy, one of those has to do with what's called data persistence. All right, so put your nerd hat on gonna be nerdy here for a moment, data persistence, that means the data existing today will last longer than the human subjects that created it. All right. And that's of course, driven by things like low data storage costs, and all the technologies that are available to allow our data to live a lot longer than us as people. So that creates a potential privacy challenge. There's another data privacy challenge. It's called Data repurposing, and that is, data that was originally created then gets used in ways that is beyond what it was originally intended. And AI is data hungry, we'll use that up, suck that up. Alright. And the third sort of area around privacy includes what's called a data spillover. And here's where, and this happens a bit in it actually drove a lot of the GDPR stuff, right, which is data collected on people who were not the target of data collection. And so of course, driving out of it was things like, you know, GDPR, out of Europe, certainly CCPA out of California, all of those things drive to or point to the need for having some regulation around it. Now, it's one thing to have regulation that's entirely different, to enforce it. And some of that comes upon us as business owners, it means that there are few things that we can and must do in order to protect the privacy of people's data and their information while still delivering value from AI. And that's that's certainly the balance that we're going for. One of the primary concerns, of course, with AI is its ability to replicate or reinforce or even amplify harmful biases, right? And this is a challenge because those biases can proliferate and then end up driving insights and and recommendations and predictions that of course, take you know, are wrong, right have have this human bias in it, there's there's another challenge to that we have with AI, let's say that we're going to try to fix that or solve for that. One of the problems, though, is that a lot of our auditing methods used today are based on the fact that something has already occurred, meaning in this case, with AI, that makes it even more difficult, right? Because it means that I've created an AI model, and I'm starting to then employ recommendations, insights and decisions, ways in which I work with people or deliver solutions, all with the incorporated bad behavior already. So it's kind of late, that doesn't mean that we shouldn't do the audits on the data. But they're post deployment by nature, meaning I've, I've already deployed it. So what we have to figure out is to find a balance, right, with privacy, as well as AI progress, it's finding the ability to say I'm gonna, I'm going to grow my my data usage in a way that that protects the privacy of the individuals involved. But I also need to allow AI to move forward and that right, there is, of course, a challenge that we're looking to pursue it some groups use consent today, right? It's a get someone to consent that they you know, you can be happy to share your information with them. That has some challenges with that those consents, not always as powerful as a tool as we might believe. And there's been examples where consent has been still misappropriated, right, what we thought originally what people thought originally was consent for certain use, then there was spill over into other areas, meaning people, you know, people didn't know their data was being used by AI for other purposes. So again, even though consent might be there, and organizations or people are well, intending, controlling, controlling the the, you know, the the boundaries of the consent, and enforcing that still is a real challenge, and relies on a lot of people to manually handle that, which means that there's more opportunities for us to mess up. I was looking at a report from the Brookings Institute, they were talking about AI Governance Initiative. And most interesting, there's this is some legislation that was pursuing this balance of how to pass privacy legislation, while while still allowing for AI to do the kind of work that it needs to bring about some of the benefits to humanity that we feel that we can do with this with this awesome technology. One of the techniques that that is mentioned here in this Brookings Institute report was, and you've heard it before, is all around what's called algorithm clarity, right? It's having clarity on how the algorithms using your information, right, that seems to be a useful piece to help dealing with it. But one of the problems with that is, you know, as an SMB owner, is that it ends up giving though, the burden typically on the backs of the of the SMB owner to say two things, one, I have to I have to make things transparent, so that my customers are aware that some aspects of their business information is leveraged by AI, right. And so that's, that's sort of the first incumbency is to say, I'm going to tell you, here's, here's what, here's what we're going to do with your data, it's going to be, you know, used in AI, and to draw the line on what information is not used. Okay? So that's what kind of comes out of this, right? It's, it's a, it's an activity or, you know, being forthright with, with our customers, on on what the intended use of the information that will or will not be used right in to draw that line. That's the first sort of consideration in algorithmic clarity. The second consideration, though, is explainability. Right. So that's, again, where you let your customers know what kind of algorithms are being used. Right. And this may include, you know, access to a human to provide that clarity, you know, okay. The thing I struggle with this, and of course, I that's all well and good. The thing I sometimes get challenged with here is what the heck does it mean to have one of the people in your team explain? Oh, yeah, you know, we use linear regression, or we use a particular classification model or, you know, a Bayes model, right, etc. We used all these different machine learning models and algorithms to that's what good is that right? 99% of people are gonna be like, What are you talking about? How did that help me understand any better? So this area of explainability, right, so the transparency Hey, we're going to use this kind of information or Not this kind of information in terms of the AI. So being clear with your customers on that. And then number two, coming up with a well Set Description for the kinds of algorithms being used, the, here's us maybe a simple way to think about it, you can break it into two buckets, right? When you're trying to explain AI to your customer say, we're going to be using this set of data for our AI algorithms. But we want to let you know that there's sort of two major areas, right. And what I'm gonna say here doesn't apply to all of AI, but for sort of vague, you know, AI for analytics, then then this applies. And it can be simply this. For those kinds of AI problems, where we're trying to determine yes or no answers, then we use what's called classification models, right? So it will be good for us to sell you this product or that product, yes or no? All right, classification kinds of problems. Then there's the other kind of problem, which is we'll use some AI algorithms to help us know, what might be the right price range, right? Now, of course, those are called more regressions, style algorithms. But you don't need to say that. It's simply we're going to use AI to help us understand yes, or no kinds of answers or questions to, you know, answer the questions. And the others, we're going to use it to understand, you know, proper pricing, perhaps right? Things that are not necessarily yes or no, but but degrees of difference, right? Those are two major buckets. And we can work on developing pretty simple language to explain this stuff. Otherwise, what good is it right if people can't, can't get it? Alright, I want to just point out one other thing here. So let me just summarize. So there's two things I think that an SMB can do to apply AI. Alright, so and to help solve for this problem of data privacy, after looking at and applying AI in multiple situations, or excuse me, over many years, come down to these two, two steps. They're a bit overly simplified, but I still think that if you print these out, put it on your wall, it could save you some real pain. Alright, so here's the first one. The first one is where I've seen a fair amount of pain. And this will sound really overly simple. First one is this. Start your AI journey with vetted questions and data oversight. Like what? Alright, I'll I'll come back to that. Number two, apply AI using smart steps. What? Alright, I'll come back to that. Awesome. Alright, so let me talk about number one here for a moment. So uh, number one here starting your AI journey with vetted questions and data oversight. It seems like an obvious first step, but when you examine the case studies of AI failures empirically, it looks like you know, this step has either been skipped or was not given the proper waiting look, a key technique here is to first vet what while you're doing this is to first bet by leveraging an independent party or going under NDA with someone, but what you want to challenge is the intended question you're trying to address with AI? Right, some of the biggest missteps with AI has been? No, that was the wrong question to be asking, this is the wrong use case to be pursuing right? There was inherently something that was either, you know, prone to lots of bias or was an unethical use of AI. Right. So in this step, the anticipated questions for AI. I know that sounds so simple, but it should be written down and evaluated in the context of the impact to your customers, and to other interested parties and to humanity for crying out loud, right? Just stop and do that simple stuff. I know, it sounds so doggone obvious. But alright, now, what does it mean to vet your AI questions? Well evaluate the AI implications to your customers, as well as look at some of those three elements that I introduced earlier. In other words, hey, will there be data persistence? What does it mean for the data that I'll be collecting to be in existence longer than the humans that created it? Right? What does that do in terms of in terms of privacy impacts or data repurposing? Wait a minute, are we going to be using the data beyond its originally you know, imagined purpose? And if so, you know, what obligation do we have to the people of all and number three data spillovers, right? Ask the question. Wait, are we collecting data on people that were not targeted those with whom we you know, initially intended? So stop and ask do I have the right question and then And then also, what's the impact of these two these three AI privacy areas of data persistence, repurposing, and data spillovers? All right, that's step one, stop and do a little vetted questioning, right and data oversight before you get too far. All right, number two is this. This in this one I call applying AI using smart steps. What this means is to iterate on the AI model and continue to refine and refactor and rebuild it as more as learned. What that does is it allows us to even adjust our AI models that might have some bias that we discover, right? So what it means is to build your vetted model, learn from experience, and then evaluate the impact to your business, your customers and then iterate. Right. So there's a book that came out not too long ago, it's by Bernard Marr. It's called "Artificial Intelligence In Practice". And what he's got in there is he's got 50 company use cases where AI was applied. Now I just want to pull something from that book, that's interesting. He goes, in that book, there's this one use case about Alibaba in China, right, who ultimately built a virtual platform that mimicked customer behaviors. And one of the reasons they did it was because it would take too long and too much effort to continually refactor their system. And so this virtual platform is used to allow the AI to continue to be refined and rebuilt and refactor. Now, you know, to do you know, to do lots of model rebuilding, in some situations, right, that's really heavy effort to do. So you either gonna have to put in the extra effort upfront to really ensure that you got the data privacy problem solved for or it well do that. And if you're able to then do the smart steps, which I found really helpful, which is, take the model Build it, try to apply it look for where a bias might be exposed, or privacy might be exposed when you didn't expect it. The lesson is this. Adjust your mindset as a business owner to refine your AI model over time, right take into consideration the changes in context, the changes in the economy, as well as lessons learned. And put in your mind that part of doing AI means that that will you know, continue to refine and improve and rebuild this AI model. Now when you combine these two steps, right, this first step is the vetted privacy aware questioning, right and looking at your data, as well as the mindset of smart steps where you simply refactor and approve you and model over time. What I found is that if you do those two things, you're in a much better position. For better privacy AI data privacy considerations. It puts you on a great path for both near term as well as long term viable business impact, you know, to your organization. Alright, everybody, thanks for joining and until next step. Until next time, use the two steps to ensure privacy for your AI that brings incremental business growth. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com now.
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CAIR 57: Interview - How AI Turns Your Sharing Into BUSINESS GROWTH
12/18/2021
CAIR 57: Interview - How AI Turns Your Sharing Into BUSINESS GROWTH
In this episode, we take a look at how AI turns your sharing into business growth. Grant Okay, welcome, everybody to another episode of ClickAI radio. So I'm very excited to have here with me today ShareThis business development leader. I think it got that right. Michael Gorman, business development leader. But before I go any further, Michael, would you introduce yourself? Michael You bet. Grant. Yeah, it's great to be here. Like you said, I oversee business development, but also product and marketing at ShareThis. I've been I've been with ShareThis for a couple of years. In that role. I have a background in data, really, data and analytics has been my passion. Also media and marketing sort of themes. I've worked for big data companies like Axiom, I've worked for an email marketing leader, digital impact, they got bought by Axiom. That's how I got there. And I've also worked for big consulting firms. And for ESPN back in the earlier days of my career. Grant Oh, wow. Could you maybe give us a play by play? I bet you could write ESPN. Interesting. Wow. Michaels It was a fun period. I was like years eight through 11 of the history of of ESPN, which, so is a fun time to be there. Grant How fun. All right. And he did some some consulting roles as well. So data and analytics, huh? Yeah. Right. All throughout all throughout the career. So what led you into this work was ShareThis what was it was the journey there? Michael Well, one thing is that, that I've worked with our CO CEO on the past, at axiom, so we knew each other, but ShareThis is a really, really special data asset. In a lot of ways, and within the world of the of the advertising that I've worked in for quite a few years. It's it was well known. So when I had an opportunity to do a little consulting for them, I jumped into it. And that led to the to the role. It's a Yeah, sure this is, you know, it's Well, shall I tell you a bit about the company? Or is that? Grant Yeah, yeah. I mean, yeah, tell me a little bit about how it got started. And its purpose and sort of the vision of it. Michael You know, well, like a lot of companies, it started with one purpose and, and things evolved a little bit over time, it, it started off in the early days of social networks, when Facebook was still a new idea and mind MySpace was, was beginning to slow down, it was with the idea of making it easy for any website to make to make it easy for their users to share content to all the social networks that they might have an interest in. And so a developer with a simple, taking, you know, taking a piece of code and pasting it on their website that they could then have sharing. We and so it was one of two or three tools that really started in those early days and became a leader in the space. We actually have a how to still maintain a trademark on that little little V on the site there. Yeah, I mean, that's what you're known for. Yeah. So it's a sign if that's there, it's a sign that sharing is you know, sharing tools are present. It's essentially the balance value for the for the publisher for the owner of the site who doesn't have to does no work to have sharing available will get some analytics as a result, sharing is valuable because it makes it attracts more people to the site new users more more content. And, and so it's it's grown up naturally. And we're, you know, so really well established. But a number of business models were tried over the years, but but about five years ago, we started focusing, moving towards being 100% about our data, is that really as a special asset, we have around 3 million publishers using us sort of our live arm 3 million now, that's been pretty stable, you know, half to three quarters and in the rest of the world, a quarter in the United States, a little biased towards English language, but we have every language in the world represented among the users on the sites. And, and so that data and and we'll talk more about this when we get into things like, you know, the the technology in the AI. Yeah, but we're really just, you know, it's like a window into what, what people are what's on people's minds? What are they looking for? What are they searching about online, and we can, you know, discern trends and also, you know, make sure that advertising is more relevant for for users. Grant So I have a question for you on that. So you've, of course, are familiar with the terminology of neuromarketing, right. And, you know, as a way of sort of tracking, how are people interacting with a site, right, and where do they go? And where do they point and click and, you know, there's organizations that look at, you know, extracting what the user is doing on the site, this feels like this starts to come into that world right that day. I mean, I don't know that it's tracking every single movement, but it's tracking, obviously, the event of I want to share something. Any thoughts on that? Michael Yeah, that's really interesting. I mean, there's a lot of different ways to make inferences about about people, we tend to focus a bit more on the on the broad, the broader picture, that the thing that's that, I mean, there's, like you say, so many choices. But the thing about online content is, it's very rich. So when a person visits a site, there's a lot of things there, there's a lot of things on the page they're looking at. And so what we've really focused on is using the page as a source of clues about what a person is interested in, we also might look at the link in and out of the page, and get a clue from, say, a search term as well, that's a that's useful, and clearly when someone shares, you know, content that's that that sort of zoned in on exactly what they care about on the page. But we've opted more for the broad picture of focusing, you know, taking all that richness and attributing some probability of interest that for you, for user to the things that are on the page. And that way we can we have just such a broad, you know, broad palette to work with. And I think also from the point of view of, of, you know, user consent and user experience, it means that what we're actually collecting is is relatively light, it's just that this user was on this page at this time. And any inference we make is not based on what he or she did, or how are their eye movement, there's no no personal collection, we just have the that event, and we get all the all the power. Grant So it's when they were there. Is it anything about how they got there? Or where are they left? Michael Yeah, exactly. We do. We do use the inbound links and outbound links when we can get them. And that sometimes, as I said, yields a search term, those can that was sort of part of the of the link the part of the information that what came with the user, you know, the referring search term or so that so there's some some useful data there as well. Grant Yeah. So so when you collect this, and then that's got to be a massive repository, I think I saw somewhere else and I'm looking at, was it three terabytes of raw data and 100 million keywords in 200 languages a day? Is that right? Michael It sounds roughly right. I haven't counted it lately. But, yeah, you're right. But But yeah, we we see about half a billion, you know, unique, what we call events, something, you know, something happened at a point in time, visits a share per day. Grant This is a grounds for, you know, a playing field for AI, right, just you have so much data. So tell me what it is you learn from it with the AI, right? What kinds of problems are you looking to solve? As you and I know, when we pursue AI, we, it would tend to be better served if we're going after a particular question or thought in mind. Now, obviously, we get surprised with AHA insights from Ai. But going intentionally after something makes a lot of sense. Can you give a scenario the kinds of things that you're looking for? Michael Well, the I would say that the theme that has worked for us so far, is to try to do is to focus on being the able to represent and reflect human interest, what are people interested in? And yeah, and so. So we, we use, and I guess where the AI comes in is that we use the latest techniques of language analysis and language modeling. So we capture all of the linguistic content on the page and then we represent it in a number of ways. What are all the prominent keywords? What are the what are the entities that are you know more that are Unusual, you know, a brand name, a celebrity name, a business name? What are the what is this page about the concept? Or what are? What are some of the concepts that accurately describe what this page is about. And then we have some standard categorization techniques are basically a taxonomy of topic interest topics that we we screen for, you know, and and it's not, it's not a yes, one of the nice things about this is it's not a, a, it's not a, it, we don't have to decide one thing, you know, we were able to say, all of the prominent keywords, and all of the interesting entities and several concepts and all the categories that this page is about. So it could be a page, it's about, you know, mountain climbing and and what shall we say? And Utah, and the, or the American West and, and road vehicles? And, you know, and beverages, you know, skiing or whatever? Right, right. Exactly. Grant Yeah, so some form of an ontology there, right, that allows you to sort of connect these together? Michael Yeah, we used a number of techniques that you said, One is, we built a custom ontology, using relative and you know, we're, we're not a huge company. So we, we try to wherever we can do something open source or free as the entry point we do that. And so we, we use some Wikipedia, it's slash DBPedia is a source for us. And, as is some Google free offerings that help us sort of the provide the raw material for building our customer ontology. We've also take great advantage of some of the latest open source language modeling tools. One is when it goes by the name of the Google released one, I forget what the what the acronym stands for, but one that's called Bert, and then more recently, one that's called Muse. Yeah, we use muse. Okay, that, that allows us to represent anything, either a word or a sentence, or the whole page as a as a set as a vector of 500 numbers. And if two pages have the same values for those 500 vectors, then they are about the same thing. Yeah, you got you have some affinity there right now, even though in practice, they might be in different languages use totally different, you know, different sets of words, but they're still about the same thing. That's, that's, that's really, for us that technology has been a real breakthrough. Because it's we've been sometimes keywords and can be very, you know, they can be false positives or No, yeah, negative. Grant I mean, there, yeah, there's nothing that governs some, you know, webpage designer to, you know, say, hey, are they using the actual right keywords? Right? Michael Yes, or even? Or even? How do you a lot of words have multiple meanings? How do you disambiguate to get the right one? Yeah. So this this, embedding technology, this Muse model helps us do that. And then Facebook is given we use a tool, they think it's called Facebook. Ai similarity search. Yeah. And both of these are open source tools, y'all you have to put in the effort and have the knowledgeable people to master their use. And that allows us because great, it's great that you've now got all these numbers you can compare, but that's a lot of numbers. That's you half a billion a day, you know, and we have we see 600 million unique pages every month. So so how do I great, I want to rank the 600 million pages to see which ones are most about skiing in Utah. Yeah, that's, you know, how do I do that quickly, and then and affordably? So fate, the Facebook tool helps us a lot with that. Grant So let me ask you a question that So so far, you've been talking about leveraging AI technologies to help you get your arms around that sheer volume of data on a daily basis and to try to extract some meaning and semantics and understanding from it. That's a good point that's on the side of ShareThis and the benefits to ShareThis. What about it from pivoted to the other side? What does it mean to it is, you know, I talk a lot with small medium organizations, how does that benefit them? What takeaways or values come over to help them through something like that? Michael Well, what the I mean, the industry that we started with, is was is advertising and programmatic online advertising as a place where we make our solution available. And so we were at this point, probably the leading source of the ability to target ads based on interest. So if if A small business were doing online display advertising and they went to Google's, if they use Google's platform or trade desk, or any of the major platforms, and they searched on, I want to find people interested in skiing in Utah, our data would be one of their choices to find that. And so it's designed to provide a broad set of individuals who in the last 30 days have shown some interest in that topic. And it could be, you know, it might be at the level of skiing, and they might, then they might, but but the nice thing about it is that we we've, I mean, it's hard, this is harder for the stats, that's what's available for the smaller business. That's, it's, it's right off the shelf, you can, you can use $1 worth or $10 worth or $100 worth if it works for you. But then on the big company side, we use some of those tools I talked about for is, well, what if, what if we don't actually have ski in Utah, we just have skiing, right? Well, we well, for an advertiser can can say, well, I need to skiing in Utah. In fact, I need to, you know, skiing in snow. But what is the alter? You know, we can create a segment using keywords and, and topics that is just about that is exactly what they need. Grant So if I were to look at maybe an advertising opportunity, leveraging, you know, this great insight that you have, does it allow me to target specific demographics, specific locations or locales? So like, you know, you're able to? Michael Absolutely, it's pretty much anything you could, I mean, because every kind of website needs sharing, we have our, our customer base, our base of publishers use our tool is pretty representative of the internet as a whole. And so if your interest is travel, we've got sites that are about, you know, traveling Las Vegas, traveling to Europe traveling to do outdoor activities, if you're interested in financial products, we can we can find things, you know, content that relates to whatever be at a mortgage or or FinTech to know. And we we represent those in about 1500 standard audiences that we distribute every day. And every day, the nice thing about our data, compared to a lot of datasets is we refresh it every day. Yeah, Michael I mean, it's every second, right? I mean, yeah, it could be, you know, people talk about real time, and we were always looking for people who've got a real time use case. But yeah, at this point, the the most frequently we refresh for a client, the customer is up by a by his hourly. Grant Oh, it's hourly, okay, that's, that's still really up to date. Yeah. I mean, if you had hourly insights on what the what's in the mind of people are the consumers that's really fresh data? Michael Yeah, yes. Yeah. Yeah, one of the areas that we that we are moving towards is trying to go beyond advertising and inform other activities like demand forecasting, you know, how much should we order for a store in a given location? Well, our data about how much interest is being shown on the products of that store, and in that store, in that area, we can sort that way, and provide that as an input. Grant That makes that makes a lot of sense. You know, there's, there's some retail organizations I've worked with with AI. And obviously, it always comes back to or not always, but most of it comes back to the supply chain, right, getting further and further left in terms of their their demand forecasting. And if they were able to understand you know, where that interest lies, it does almost gets to, oh, I know, this is a stretch in terms of language, but it's kind of a sentiment analysis, a play on that. Right. It's the ability Yeah, the ability to say I understand what the sentiment is in terms of where their interests are. And if I understood what that was, in terms of particular set of products or other things I'm offering, and I could get that further into my, into my supply chain, that would be really valuable to Yeah, Michael I mean, it's nice that you mentioned that we do we do actually score the sentiment of the content on the page. So we're sentiment is useful, either to only talk to the people who are in favor or opposed or the middle, we can we can build an audience that or provide that as a data element as well. Grant Yes. See, that's that's powerful to understand the the sentiment of the page itself, even how people are talking about it, or what they're doing, have you ever ran into the ability to use it in terms of IP tracking, right. So in other words, if there is an organization that had a certain set of IP and, and and really, yeah, they felt like oh, my IP, I've lost control my intellectual property, it's showing up in other places. Michael Oh, that's interesting. You know, I was thinking of I was thinking of the I the the IP address the Internet Protocol address. Yeah. Should have been more clear. Yeah, I'd love to answer that question. But that wasn't what you were asking. Well, yeah, answer. Oh, we'll start with intellectual property. Yeah. One sec. Regarding intellectual property? You know, we have it. Let me think about that. Let me give you the scenario. I had, one of the things I've thought about that we haven't taken on it, you know, is that is, is using using intellectual property as a data set? Yeah. If if we were to, to read to do the same kind of analysis I talked about earlier on trademarks. Yeah, it could mean be the means for discovering which, what sites were about branded products by seeing the correspondence between the trademark and the, because that's always you run into difficult How do you tell something's a brand? When is Jaguar a brand? You know? Exactly. Grant Yeah. Yeah, it's a fascinating problem. I had a company reach out to me and say, Hey, can you develop something in this area, and we did some work on that. I called it smart catch, but they were looking to protect their IP, their intellectual property, which was, we've got this corpus of information. And, and we've got others that are, you know, getting access to it and are promoting it, you know, elsewhere out into the, you know, online universe there, or metaverse. And, and I want to be able to discover, you know, when it's opportunistic, and you can use, you know, SERP and other technologies to try to find some of that stuff and do lots of scraping. But that's got its own challenges in terms of a solution. And where you've got this opportunity to listen. Right, right, to observe what people are sharing and to the to compare that against a corpus of protected material, right? Michael Kind of an intro you're giving, you're giving me a product idea. Seriously, one of the things that we've done this year, is to create what we what we call, you know, similarity scoring. So similarity, and that's gonna cause Yeah, you can literally give someone who was curious about the dispersing dispersion of intellectual property, give us a domain. Yep. And, or a, you know, the piece of content that describe their, their stuff, and we would rank our sites for which ones had it most. Right. And, you know, whatever the top 100, you know, and you know. Grant What I found interesting on that, when I built the initial piece on that was that I found that, in some of the discovery,...
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CAIR 56: Interview - How AI Ethics Affects Your Business !!
12/14/2021
CAIR 56: Interview - How AI Ethics Affects Your Business !!
Welcome to ClickAI Radio. In this episode I have a conversation with some AI experts on how AI ethics affect your business. Grant Okay, welcome, everybody to another episode of clique AI radio. Well in the house today I have got a return visitor very excited to have him and a brand new person. I'm excited to introduce you to Carlos Anchia. I've been practicing that I get that right, Carlos. Carlos Sounds great. Good to see you again. Grant Even old dogs can learn new tricks. There we go. All right, and Elizabeth Spears. Now I got that one easily. Right, Elizabeth? Elizabeth You did it? Yeah. I'm really happy to be here. Grant This is exciting for me to have them here with me today. They are co founders of plain sight AI. And a few episodes ago, I had an opportunity to speak with Carlos and he laid the foundation around the origin story of AI for vision, some of the techniques and the problems they're solving. And I started to nerd out on all of the benefits. In fact, you know what, Carlos, I need to tell you, since our last conversation, I actually circled back to your team and had a demo of what you guys are doing. And yeah, I think it was very impressive, very impressive, you know, a guy like me, where I've coded this stuff. And I was like, Oh, wow, you just took a lot of a lot of pain out of the process. You know, one of the pains that I saw come out of the process was the reduction in time, right that how long it would take for me to cycle another model through it. That was incredible, right? I can't remember the actual quantification of time, but it was at least a 50% of not even 80% reduction of cycle time is what I saw come through, there's even model versioning sort of techniques, there's just, you know, there's another really cool technique in there that I saw. And it had to do with this ability to augment or, or approximate test data, right, this ability to say, but but without creating more test data, it could approximate and create that for you. So now, your whole testing side just got a lot easier without building up, you know, those massive test cases and test basis for for doing the stuff So, alright, very impressive product set. And let's see, Elizabeth can you explain that? Elizabeth That's right, Chief Product Officer. So basically, kind of the strategy around what we're building and how we build it. And the order in which we build it is is kind of under my purview. Grant Okay, very good. Awesome. Well, it's so great to have both of you here today. So after I spoke with Carlos, last time, after we finished the recording, I said, You know what, I want to talk to you about ethics about AI ethics. And so as you heard in my previous podcast, I sort of laid the foundation for this conversation. And it's not the only areas of ethics around AI, but it's a place to start. And so we want to build on this. And we're gonna talk about these sort of four or five different areas just to begin the conversation. And I think this could translate certainly into other conversations as well. But to do that, could could one or both of you spend a little time giving the foundation of what is AI ethics as a relates to computer vision itself? What are some of the challenges or problems or misunderstandings that you see in this specific area of AI? Carlos Sure, I can take that one. So I think really, when we're talking around ethics, we're bowling any sort of technology, we're talking around how that technology is implemented, and the use of that, right and what's acceptable. So in the case of this technology, we're talking around computer vision and artificial intelligence, and how those things go into society. And it's really through its intended use on how we evaluate the technology. And I think really, computer vision continues to provide value to allow us to get through this digital transformation piece. As a technology, right? And, you know, once we start with, yes, this is a valuable technology, the conversation really now shifts to how do we use that technology for good, some cases bad, right? Where this is where that conversation arises around, you know, having the space to share what we believe is good or bad, or the right uses or the wrong usage just right. And it's a very, very gray area, when we look to address technology and advancement in technology against a black and white good or bad kind of a situation, we get into a lot of issues where, you know, there's a lot of controversy around some of these things, right, which is really, you know, as we started discussing it after the last podcast, it was really, you know, man, I really need to have a good podcast around this, because there's a lot to it. And you clearly said there was a previous one. And now there's this one, you know, I hope that there's a series of these so we can continue to express value and just have a free conversation around ethics in artificial intelligence. But really, what I'm trying to do is set the context, right. So like technology works great from the just the science of the application of that technology. And if you think of something like super controversial facial recognition, now, absolutely. I don't want people to look at my face when I'm standing on a corner. But if there's, you know, child abduction cases, yes, please use all the facial recognition you can I want that to succeed really well. And we've learned that technology works. So it's not the solution itself. It's how we're applying that solution. Right. And there's there's a lot of new ones to that. And, you know, Elizabeth can help shed a little bit of light here, because this is something that we evaluate on a constant basis and have really free discussions around. Grant Yeah, I would imagine you have to even as you take your platform into your into your customer base, even understanding what their use cases are imagined, at times, you might have to give a little guidance on the best way to apply our uses. What have you seen with this, Elizabeth? Elizabeth Yeah, you know, there's, it's interesting what Carlos is saying there's a lot of the same themes for evaluating the ethics and technology in general are similar ones that come up with when AI is applied. So things like fraud or bias is actually more can be more uniquely AI. But that absolutely exists in other technologies. And then inaccuracy and how that how that comes up in AI, and then things like consent and privacy. So a lot of the themes and we can we can talk about how AI applies to these, but a lot of the themes that come up, are really similar. And so one of the things that we try to do for our customers is, especially kind of your listener base, that's that small, medium businesses is take a lot of that complexity out of the, like, Hey, I just want to apply, you know, I just want to solve this one problem with AI, what are all of these concerns that I, you know, I may or may not know about. So, we try to do things like build, build things into the platform that make it so something like bias. So, for example, is usually comes down to data balance. So if we provide tools that really clearly show your data balance, then it helps people make unbiased models, right, and be confident that they're going to be using AI ethically, Grant So that I'm sure you're aware of this Harrisburg University in Pennsylvania case where they ended up using AI to predict criminality using image processing, right. And, of course, that it failed, right? Because it you know, looking at a an image of someone and saying, Oh, that person is a criminal, or that person's not a criminal. That's using some powerful technology, but in ways that, of course, has some strong problems or challenges around that. How do you help prevent something like this? Or how do you guide people to use this, this kind of tool or technology and in ways that are beneficial? Elizabeth Yeah. What's interesting about this one is that the same technology that causes the problem can also help solve the problem. So so when you're looking at your corpus of data, you can use AI to find places where you have data in balance and and just to kind of re explain the what happened in that case, right. So they had a data imbalance where it was Miss identifying Different races that they had less data for. So, you know, a less controversial example is if we're talking about fruit, right, so if we have a dataset that has 20, oranges, two bananas and 20, apples, then it's just going to be worse than identifying bananas, right? So one of the things that that can be done is you apply AI to automatically look at your data balance and say, and surface those issues where it can say, hey, you have less of this thing, you probably want to label more of that thing. Grant So I'll try to manage the data set better in terms of proper representation. And try finding, finding bias is a real challenge for organizations. And I think one of the things that your platform would allow or unable to do is if you can take off the pain of all of the machinery of just getting through this and and free up organizations time to be more strict in terms of evaluating and finally, oh, taking the time to do those kinds of things, I think you might have an opportunity to improve in that area meeting customers might be able to improve in there, would that be a fair takeaway? Elizabeth Yeah, it's something that that we're really passionate about trying to provide tools around. And, and we're kind of prioritizing these these tools. The other one is, is that has to do with your data is as well is finding inaccuracies in, in your models. So the one example is X ray machines. So they did. They've basically they had an inaccuracy in a model that was finding a correlation, I think it was for it was for the disease detection. So it was finding a correlation just when the X ray was mobile, versus when they went into kind of a hospital to get the X ray. And so, you know, these models are in many cases, really just very strong pattern detectors, right. And so one of the things that can really help to, you know, to prevent something like that is to make it easy to slice and dice your data in as many ways as possible, and then run models that way. And make sure that you aren't finding the same correlation, or the same sort of accuracy with a different data set, or a different running of the model in a different data set. So said, in other words, you would be able to say, I'm going to run all of the portable X-ray machines versus all of the hospital ones, and see if I'm getting the same correlation as I am with, you know, cancer versus not cancer, or whatever they were looking for. Grant A quick question for you on this. So in my experience with AI, I have found sort of two things to consider. One is the questions that I'm trying to get answered guides me in terms of, you know, how I prepare the model, right? I'm gonna first lean towards certain things, obviously, if I want to know that this is a banana, right, or an apple or what have you. So the kind of question that when I answer leads me to how I prepare the model, which means it leads me to the data that I select. And the question is, is do I do I? Should I spend the time really putting together the strong set of questions? And rather, rather than do that, just gather my data? And then and then execute that data, the build a model? And then Ben, try to answer some questions out of that, you see what I'm saying that way, maybe I'm not going to introduce any bias into it. Elizabeth So we we encourage a very clear sort of understanding of the questions that you want to answer, right? Because that helps you do a few things, it helps you craft a model that's really going to answer that question, as opposed to accidentally answering some other questions, right. But it also helps you right size the technology so far, for example, if you're doing if you're trying to answer the question of how many people are entering this building, because you want to understand, you know, limits of how many people can be in the building or, you know, COVID restrictions or whatever it is, that that solution doesn't need to have facial recognition, right. So to answer that question, you don't need you know, lots of other technologies included in there. And so yeah, So, so defining those questions ahead of time can really help in sort of a more ethical use of the technology. Grant So one of the first jobs we would then have a small medium business do would be get clarity around those questions that actually can help us take some of the bias out. Is that a fair takeaway from what you share? Elizabeth Exactly like the questions you're trying to answer. And the questions you aren't not trying to answer can also be helpful. Grant Oh, very good. Okay. All right. So all right, the opposite of that as well. All right. So while we could keep talking about bias, let's switch to something that is that I think comes right out of the movie iRobot, right. It's robot rights. Is this, is this a fluke? Or what, you know, is this for real? I mean, what do you think? Is there really an ethical thing to worry about here? Or what? What are your thoughts? Elizabeth You know, in most of the cases that I've seen, it's really more like, it comes down to just property, like treating property correctly, you know, like don't kick the robots because it's private property. So not really around sort of the robot rights but you know, some already established rules be in for the most part, I see this as kind of a Hollywood problem, more than a practical problem. Grant Maybe it makes good Will Smith movies. But other than that, yeah, fighting for rights, right. Now that seems like it's way out there in terms of terms of connection reality. Okay, so we can tell our listeners, don't worry about that for right now. Did you add something back there? Carlos Just an interesting point on the robot rights, right. While while it's far in the future, I think for robot rights, we are seeing a little bit of that now today. Right? When like Tesla AI day, when they came out, they decided that the robot shouldn't run too fast that the robot shouldn't be too strong. I think it's a bit. It's a bit interesting that, you know, we're also protecting the human race from for us building, you know, AI for bad and robots for bad in this case. So I think it's, it's, it's on both sides of that coin. And those are, those are product decisions that were made around. Let's make sure we can run that thing later. So I think I think as we continue to explore robots AI, the the use of that together, this topic will be very important, but I think it's far far away. Grant I'm wondering is that also blends into the next sort of ethical subtopic we talked about, which is threat to human dignity. And it might even crossed into that a little bit, right, which is, are we developing AI in a way that's going to help? protect the dignity of human certainly in health care situations? That certainly becomes important, right? You probably heard on the previous podcasts that I did, I played a little snippet from Google's duplex technology that was three year old technology, and those people had no idea. They're talking and interacting with AI. And so there's that aspect of this. So where's the line on this? When? When is it that someone needs to know that what you're interacting with is actually not human? And then does this actually mean there's a deeper problem that we're trying to solve in the industry, which is one of identity, we've got to actually create a way to know what it is that we're interacting with. And we have strong identity? Can you speak to that? Yeah, Elizabeth I think I think the there's two things that kind of come into play here. And the first is transparency, and the second is consent. So in this case, it really comes down to transparency, like it would be very simple in that example, for that bot to say, Hey, I'm a bot on behalf of, you know, Grant Larsen, and I'm trying to schedule a hair appointment, right, and then going from there. And that makes it a much more transparent and easy interaction. So I think in a lot of cases, really paying attention to transparency and consent can go a long way. Grant Yeah, absolutely. All right, that that that makes a lot of sense. It seems like we can get around some of these pieces fairly, fairly simply. All right, Carlos, any other thoughts on that one? Carlos The only thing there and then touches on the stuff you guys were talking about on the bias piece, right? We're really talking about visibility and introspection into the process. Right. And with bias, you have that in place, right? We can detect when you know there's a misrepresentation of classes within the the model. In some cases, there's human bias that you can get that right but it's it's having that visibility in the same case with the threat to human data. With that visibility comes the introspection where you can make those decisions. You see more about the problem. Grant Mm hmm. Yeah, yeah. So if we were to to be able to determine we have a bad actor, if there's not transparency, that would be a way that we could help protect the dignity of humans through this. Alright. That's reasonable. All right. So let's move on to again, sounds Hollywood ish, but I'm not sure it is weaponization of AI. Right? What are the ethics around this? I'll just throw that one on the table. Where do you what do you want to take that? Carlos, you wanna start with that one? Carlos Sure. I mean, so weaponization and and I think when we talk about AI and, and the advancements of it, you quickly go to weaponization. But really, weaponization has two different pieces to it, right? It's obviously it depends on which side of that fence you're on, on whether you view that technology is beneficial or detrimental. But in some cases, that AI that same technology that is helping a pilot navigate, it also helps for a guided missile system or something like that. So we really have to balance and it goes back to use cases, and how we apply that technology as a people. But you know, weaponization, the rise against the machines, these kind of questions. While they're kind of out there. They're affecting society today. And we have to be able to have productive conversation around what we believe is good and bad around this while still allowing technology to succeed. So there's a lot of advancements in the weaponization and AI in that space, but it's really, I think we have to take it on a case by case basis, and not like a blanket statement, we can't use technology in these ways. Grant Interesting thoughts? What are your thoughts there? Elizabeth? Elizabeth Yeah, you know, I it makes me think of sort of turning it on its head is, is when is it? You know, when is it unethical not to use AI, right. And so, some of those questions come up when we are talking about weaponization, you can also be talking about saving human lives and making it safer for them to do some of these operations. And and that same question can come up in some of like, the medical use cases, right? So here in the US, we have a lot of challenges around being able to use AI in medical use cases, and there's, and there's some where you can have really good human oversight of the cases, you can have sort of reproducibility of those models, they can be as explainable as possible. But it's still really, really difficult to get FDA approval there. So I, again, I think there's two sides to that coin. Grant And, yeah, it's it's an interesting conversation have stuff wrong, because like, in that medical case, you talked about, you could see the value of using the same kind of technology that would be used to identify a human target, and then attack it, you could take that same capability, and instead use it in a search and rescue sort of scenario, right? Where you're flying something overhead, and you're trying to find, you...
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CAIR 55: Artificial Intelligence Ethics - Where is The LINE ??
12/04/2021
CAIR 55: Artificial Intelligence Ethics - Where is The LINE ??
In this episode, we take a look at the question where is the line for artificial intelligence ethics? Alright, everybody, welcome to another episode of click AI radio. So ethics, what are they? Well, you know, if we look at Google definition here, right moral principles that govern a person's behavior, or conduct or con or the contacting of an activity. Alright, so I'll give you an example here, right? Without going into some again, some of my business law classes that I took in college. Here's, here's an example. I was in college and my brother came into town to visit and said, Hey, let's go skiing. Oh, sorry. I said, my brother, I've got to work. He says, Hey, no, come on. I'm in town. Let's go skiing. So what did I do? I lied, I said to my boss, I don't feel well. And I went skiing. Well, to make matters worse, I'm up skiing, and I get hurt. To make things even more embarrassing. As I come down off the hill being pulled by the ski patrol. They open up the sled there, the local TV news station was there interviewing and well, I showed up on the evening news. While my boss is watching the news. He sees me there. All right, what a way to learn a life lesson. So what I did was unethical. I don't know that I have to go deeper than that. That was unethical. That was 35 years ago. I sure hope I learned my lessons since then. That was a painful life lesson. He called me that night. And he said that grant, I hope you're feeling better now. I said, Oh, yeah, yeah, I was in pain. Alright, pain both physically as well as internally. Alright, so now let's talk about since apparently some of us carbon based beings have struggled or do struggle with ethics? What does it mean to do this for artificial intelligence? Well, to do that, I borrowed four categories from Wikipedia, talking about this area of artificial intelligence, ethics, number one, category number one, bias in AI, Category Two, robot rights, category three threat to human dignity, and category four weaponization of AI. Alright, so let's take a look at each of these briefly. So as it relates to bias in AI, right, this is where, as us humans, as we build these models, these AI models, then our own biases can either intentionally or unintentionally get incorporated. And what that does is that drives downstream decision making that's bias in AI, we'll look a little bit further that in a moment, robot rights so this is of course, the idea that humans have while we've got you know, moral obligations, we have them or we'll have them to our machines as well. Might be somewhat akin to animal rights. So alright, that's robot rights. Number three, again, was threat to human dignity. And of course, this is in the areas where respect and care and compassion and another human attributes are needed, right, AI should not be used, certainly to replace replace people. So how do we help protect that? And then the fourth area weaponization of AI, this is of course, using AI in military combat scenarios or, or other kinds of scenarios like that. Alright, so what I'm not going to talk about here, though, is and I think this is a separate episode, there's the concept of singularity, right? It's the notion that that we that some self improving AI becomes so powerful that humans can't stop it kind of like the movie eagle eye or iRobot with with Will Smith. Alright, so we're gonna park that one, put that over to the side. There is a nonprofit organization, however called Ready big breath, the partners the partnership of AI to benefit people and society is formed by Amazon, Google, Facebook, IBM, Microsoft, Apple, all the biggies. They're obviously looking at to develop the best practices in In AI ethics, all right, so you want, you might want to look them up, take, take a deeper view on them. Let's go a little bit deeper on each of these categories here for just a moment. So first of all bias in AI, as you've probably heard of this came out of toward data science.com. They, they pointed out an experience in 2019, where researchers found that an algorithm that had been used on over 200 million people in the US around hospitals, it was being used to predict the likelihood that someone needed extra medical care. And without going further into it, it ended up breaking it along the lines of race, black versus white, now comes to find out that what they discovered is that the data itself, the way in which was prepared, started to expose that sort of bias in the way it was being interpreted, and it translated into, you know, discriminate behavior. So that was quite quite a painful lesson. The good news is, is that they looked into it and caught that if they hadn't have looked into it or caught that then that would have translated into obviously, even worse, long term behavior. Here's another example. This comes from Compass see Oh, MPa, s, this was the correctional Offender Management profiling for alternative sanctions, long sentence, there are long title. There's an algorithm there that was being used to predict the likelihood that a defendant would become a repeat offender in the in the correctional systems there. And of course, coming out of there it translated incorrectly that a certain class or race of people was going to translate into twice as many false positives for repeat offenders as others that weren't of that race. So again, I yeah, not good, right. Ai bias is what that's about. So the questions are, what are the best practices to preserve the fair balanced use of AI? And how do you vet your original assumptions to avoid these kinds of mistakes? I find oftentimes, as organizations get focused on their question, or the problem they want to solve, get so so dedicated to solving that, that often don't stop to step back and look back at those questions, challenging the original assumptions on that. Alright, so bias in AI. Definitely a challenge and very relevant to small to medium business owners today. Alright, let's, let's take a look at robot rights. Alright, so this apparently came out around 2017 After an EU Parliament report, proposed reasonable approach to dealing with this right now. Here's the there's an article by an attorney that specialized in this from some of the research that I saw out of different reports some of it from did Jin No, comma. I said that wrong, as well as a CNBC report, both pointed out that there's this attorney that is specializing in business law and IP that argued for extending workplace protections to robots pointing out that people are kicking the robots, right that, you know, they're pushing them around, right? So for example, some are some of the stated look. And here's what's driving that argument by 2025. Some predict that robots and machines driven by AI are gonna are gonna perform half of all productive functions in the workplace. Holy smokes, I don't know, it's 2021, almost 2022? I don't know I've done enough AI right now to know, I don't know if that's really the case. That's half of all productive functions AI. Anyway, whether or not you believe that, when it's not clear, what is not clear is whether the robots will have any worker rights. And again, they pointed out that people feel hostility to him will kick over robot police resources or knock down you know, delivery bots, things like that. I've certainly seen some of that. So. So the question is, to what degree do you see this raised in the minds of people and where is the line for robot rights? And what does that look like? I'm pretty sure I Robot is not a documentary. Alright, here we go. Let's move on to number three, though. threat to human dignity now. Now, this one is really very sensitive, obviously. It's the whole notion of human dignity, right? It's the fact that humans possess some intrinsic value that caused them or says, hey, you know, they're worthy of respect, regardless of age, ability, status, gender, ethnicity. I subscribe to that. That makes total sense to me. A few years ago, Google announced a system this is I think back in 20. 18 An AI system with human sounding voice interactions. And in this particular case, I'm going to play an interaction for you. It's interesting, you can get this off off of Google site. So this is their, their material. I'm just going to take a clip of it here and share this. And tell me tell me what you think this is kind of interesting. I'm gonna pause right here. ... Okay, so I didn't play the whole thing, but pretty incredible how lifelike how human like that voice sound, and it was generated off of the Google duplex system. So the question is, did duplex reduce the human dignity? In this case of this? This assistant, right, who is trying to figure out scheduling for for the salon appointment? Right. So was the dignity reduced? And and of course, there are other variations of this, right? Where, where AI can then in behave, you know, acting behalf or as though it's a human? Where's the dignity for that for the people and let alone in, in a healthcare situation? Right? What would that look like? Those are difficult questions, certainly to answer as they go to this next category. weaponization of AI, right? Immediately in the minds of some there's this notion of, you know, the whole the whole singularity notion, right? That AI becomes in control, right? And people fantasize about that part, for sure. The US Department of Defense calls weaponized AI algorithmic warfare. That's, there's this interesting article on think ml.ai that discusses some of this. So there's a category of this warfare called lethal autonomous weapons systems, le Ws and the whole notion is that you know, autonomous weapons that can locate and identify and attack and, and kill human targets. And again, this sounds like the Tom Cruise movie Oblivion, right. In fact, I saw recently, session on 60 minutes, they aired something discussing the US and Australia's relationship with China, and pointed at a company that was producing weaponized drones as part of that puzzle. So the question is a where, where does weaponization of AI break ethical boundaries? Right? Or by definition, if you use AI for weaponization? Is it inherently unethical? Or you know, quite frankly, if AI is being used in a head up display of an Air Force pilot to improve decision making, saving the pilots life? Is that unethical? Boy more questions, and then there are answers. This area's fascinating to me, because the world's changing so quickly in this area. There are many, of course challenging questions to be addressed. Obviously, I've only scratched the surface here. But I wanted to let you know that in a future episode coming up soon, I've invited some guests from some AI companies to further discuss this topic and bring in various viewpoints. So in this particular episode here, I want to lay the groundwork for it. But to wrap up here, I wanted to bring it back to the premise of this podcast channel, which is, what does it mean to you as a as an owner as an SMB owner, right? Someone's trying to run your business and you're trying to apply AI in these four categories that I briefly touched? What does that mean to you today? Does it have immediate impact? My take on it is this. As it relates to bias in AI? I think that this one has the most immediate effect on you as a business owner today. And to help address it, it means we have to ensure that we're asking the right questions, not only the questions that we want to get answers to immediately for our business, but we need to be able to have the discipline to step back and evaluate the broader context in which we're pursuing it. It also means that we need to course prepare data, the data sets that are representative and are not skewed. So those are several things today that that can be done now, in the second category of robot rights. I don't think that that's a direct impact for right now. But you know, in the future perhaps the third category, threat to human dignity. I think this is a challenging one. Now, you know, when we've got things like deep fake, and tools like duplex, and that was a 2018. And here we are, you know, three and a half, four years since then right? You can imagine how far this is. So with deep fake and duplex and other such technologies where deceit or potential deceit can grow. I think ascertaining identity is crucial to your business. And this will grow over time. There's already been instances of AI driven technologies that have faked out business executives. So I do believe this is an immediate one. And then weaponization of AI. It's not a direct impact now, but you can see it's growing one. It's something that we need to watch, obviously, and address some more. All right, everybody. Thanks for joining and until next time, brush up on your AI ethics so you can put your business and your customers in the right lane. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. 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CAIR 54: Interview - Can AI See Better Than Humans ??
11/20/2021
CAIR 54: Interview - Can AI See Better Than Humans ??
In this episode we look at can AI help me see better in a cost effective way! Grant Everybody, welcome to another episode of click AI radio. Okay, I have in the house today with me, someone I've been very excited to talk with. He and his organization reached out to me and I was quite surprised when I saw the cool AI solution that they have been bringing to the market. And Carlos has been giving me a little background on this. And I think you'll be excited to hear what it is he's putting together. But first and foremost, welcome, Carlos Anchia. You got Yeah. All right. There you go. Carlos, please, welcome and introduce yourself. Carlos Hey, Grant. Thanks a lot for having us on. Like you said, my name is Carlos Anchia. I'm the CEO of Plainsight AI. And we're bringing to market an end to end computer vision AI platform. I'm really, really happy to be here love talking about AI, computer vision, and how we can get more people to use it. Grant So okay, so tell me a little bit about what got you going down here. As you and I were just chatting a moment ago, there's so many components to AI, or it's such a broad range of technologies there. What got you thinking about the CV or the computer vision space? What problem? What How did you get started there? Carlos Yeah, that's a really good question. So like you said, AI, the breadth of AI is huge, you have deep learning, you have machine learning, forecasting, prediction, computer vision. And these are just a few. There's a lot of different applications for AI and places you can go down and succeed in. From our respect, we really, we really focus in on computer vision, specifically how to apply that to imagery and video. Today, there's a huge amounts of data going throughout the internet and in enterprise storage classes, where you can't really extract the value of that data unless you actually perform some sort of computer vision machine learning on that type of data. So we're really extracting the value of the picture or the video. So it can be understood by machines. So think of a dog and a cat in a in a picture, right? Those cases, the machine doesn't know it's a dog and a cat, you have to train it. And that's where computer vision comes in. And really, we got into it because we were pulled in by customers, customers of ours wanted to start doing more computer vision and leveraging our platform that we had around high throughput, ingestion, and event driven pipelines. So these customers came to us and hey, you know, this is great, we'd love to really use this for computer vision. And the more and more that kept happening, we kept retooling around the platform. And finally, the platform from end to end is purpose built to do computer vision technology. And it really allows us to focus in on on what we're good at today. Right? And that's really delivering value within the computer vision space. Grant So I remember the first time I wrote some of the OpenCV framework code, right. And that was my first introduced introduction to it. This is a number of years ago. And I started thinking, Oh, this is so cool. So I'm writing all this Python code, right, building this stuff out. And then I'm thinking, how many people you know, are actually leveraging this platform and look at even though open CV is cool, and it's got a lot of capability, it still takes a lot, you know, to get everything out of there. So can you talk about how you relate to that open CV? And what is it that you're doing relative to that? And how much easier do you guys make this? Carlos Yeah, so I mean, you hit the nail on the head there, right? So from a developer perspective, it's really around, I need to learn open CV, I need to learn Python, I need to learn containerization I need to learn deployments. There's a variety of different companies that, you know, they're all great in their own right, right. Every one of those companies that we just talked about organizations are contributing tremendously to AI. But from a developer's perspective, you really have to learn a little bit of everything to be able to orchestrate a solution. And finally, when you get to, hey, I use AI. Let's pretend we're looking at strawberries. Hey, look, I built a model that the Texas strawberry that is your over the moon excited, but the very next thing is around, okay, how do I take that and deploy it 1000 times over in a field across the world and understand how to make that in an operational fashion where you know, it can be supported, maintained update, and that's really where we have this this crux of an organization where it's really different building something on a on a desk for a one time use. And and there's a lot of wins through that process. But then taking that and operationalizing for business driving revenues driving corporate goals around, why would that feature is being implemented, that's really where we come in, we want to be able to take off that that single single path of workflow where it's a little bit of everything to orchestrate a solution, and provide a centralized place where other people, including developers can go and help build that workflow in a meaningful way where it's complete. Grant So operationalizing, those models, I find, that's one of the biggest, or the most challenging aspects to this, it's one thing as you know, to, to build out enough to sort of prove something out and get some of the initial feedback, but to actually get it into production. I think I saw MIT not long ago, maybe this a year ago, now, they had come out with this report, it was through the Boston Consulting Group as well, they'd mentioned something about, hey, you know, 10% of organizations doing AI are getting return on their investment. And, and, of course, when you look at all of the investment of the takes for the business to really stand up all the data scientists and all the ML work. And you can see why the numbers translate that way. So to me, it feels like not only doing this in the area of CV, but the problem you're really trying to solve it feels like is you're attacking that ROI problem, which is you could take this kind of capability into business say you don't have to stand up all of these deep technical capabilities. Rather, you can achieve ROI sooner than rather than laters. Is that Is that accurate? Carlos That's correct. And I think it's really through the adoption of technology and you hit a you hit a really strong point for us there around the the difference between it works and it's operational. That's that's really the path of your your, you're less there in the CV world and more there with the DevOps ml ops portion of it, getting machines running consistently, with the right versions of deployment strategy, that latter half of it, just as important as the model building pieces of it. But even after you get to that piece, you need a way to improve, and improvement in the model is very costly if it's not automated. Because I mean, you can just look at the the loss for a simple detector, like a strawberry, where, you know, if the model starts to perform poorly, you're not pulling as many strawberries out of the field. So you need a way to be able to update that model, quickly, get training data into a platform and push a new model back out. And it's really around how fast you can go end to end with that workflow. Again, and again. And again. And again, this is that continuous improvement that we have born into us from previous software development life, but really in in machine learning and computer vision, your ability to train, retrain, and redeploy. That is where you really get the benefit out of your workflow. Grant Well, that really confirms my experience with AI will. Typically I'll refer to the term that we've been using, as we call it a SmartStep. It's that notion that I need to be able to refactor my models and take in consideration that changed context around me, whether it comes in from the world or from the customer, or whatever that means, some level of adjustments taken place that begins to invalidate my previous AI model. And I need to be able to quickly make those adjustments. That's fascinating. How long typically does it take for you to do that kind of refactoring of your models? Is that Is it a day? Is it a year, a month? Or the answer is? Well, it depends. Carlos So it's twofold, right? So it's, it's hours to do that. But it really depends on the complexity of the model, and how long you have to train. But in an automated workflow, you're you're continuously adding data to your training set, that are lower quality predictions, where you can retrain automatically when you hit a certain threshold, and then validate the model and push that back out into your production alized environment. So it's it when you go to develop these sort of workflows. You really have to start with whatever I build, I know I have to improve on later. So that improvement cycle ends up costing a lot if it's not part of the initial discussion around how do we count strawberries, right? So it's evident you and I can nerd out on this. Let me shift the focus a little bit and ask about it from say your your customer Write from their perspective, what is it that they need to be able to do to be successful with your solution? What skills or capabilities do they have to bring to the table? Yeah, and I think it's, I think I have this conversation a lot with our clients. And it's really less about them having technology around data science and building model, and more around a collaborative environment, where organizations, you know, they have a culture of success. But that culture of success is really borne by holding hands through the fire, it's, it's being able to commit and lean in when the organization sees something that's really important to them, either either from a technical perspective or revenue perspective. And it's these companies and these types of people that get to rally around a centralized platform where they can build and collaborate with machine learning computer vision applications. And, you know, it's it's a, it's really interesting to see the companies that succeed here, because it's really based on a culture of winning, right, where the wind doesn't have to be the hardest, most technical, logically difficult problem, because complexity really drives timelines. And if you're looking to change from an organization's perspective, start getting the little wins, get the little wins, start having some adoption within the company around, wow, computer vision is working. We've identified these problems in a few hours, we have a solution deployed, you start building this sense of confidence in the organization where you can take on those larger tasks. But you have to start with a build up, you can't just go right to the highest ROI problem. No one starts at human genome sequencing. Grant Have you, or do we got a problem? Yeah. Back up, back up. So So all right. So it means to me it sounds like as an organization to succeed with this getting my problem definition, understood or crisply put together first, what would be an obvious thing to do? But how long does it take for me to iterate? Before I know that I've got value, that I've pursued the right level of the problem? You You made an interesting comment a minute ago, you're like, oh, within a couple hours, I could potentially retrain the model and have that back operationally. That means if I can fail fast, right, if I can pick my problem space, get something out there operation, try it fail fast, and then continue to iterate with AI as my helper that that's really, really quite powerful is that the model that the your person? Carlos It is the model? That's exactly right. And it's not just hours to retrain, it takes hours to start, right. And just to highlight you kind of started with, we have to define that problem set first. So even after we define that problem set, a lot of times we have to go back and redefine that problem set, and really the piece around failing fast. It's it's experimentation. And do we have the right cameras? Do we have the right vantage point is the model correct, you want to be able to cycle as fast as you can through that experimentation phase. And sometimes you have to go back and redefine that problem set. Because you're learning more as you go, right? And you're evolving into okay, I now understand the corner cases a bit better. And with the platform, you really can cycle that quickly. I mean, machine learning at scale is really how fast you can iterate through improvement. Grant It's quite, I think it's quite a testament to how the AI just world in general is improving. I know that you and I were talking earlier, years ago, you know, when I first started writing some TensorFlow code and Keras code, you know, the, the time it took to fail was much longer, right. And then the cycles were huge and, and getting this down to a matter of hours or even a few days, you know, for an enterprise's is massive. What's the, from what you've seen terms of different industries? Are there certain industries that tend to be leaning into this and adopting it or the is there no pattern yet? Carlos No, there's a there's a definite pattern. And in 2022, we'll all see kind of what that what that's looking like. And it's really an industry that has traditionally not been able to go through that digital transformation. So think of think of think of a piece that's a very manual piece, right, like physical inspection, where humans would look at something, they'd write down their notes on a piece of paper, then that that item would go through either pass or fail or some criteria for rework. That's all possible. Now with computer vision years ago, that was impossible the accuracy wasn't high enough, plain and simple. It just took it wasn't, it wasn't better than a human. Now we have models that are better than a human for visual inspection. And these industries are digitizing their workflow. So it's not only the feature of computer vision, but it's also now I have a digital record of all the transactions, I have extracted video information, it makes auditing easy for those sectors that have a lot of regulatory compliance, those that require proactive compliance to audit requirements, as well as visibility. Visibility has always been an it's funny when we talk about visibility, but it's computer vision, but like a lot of human processes, that there's zero visibility in it there, it's really difficult to audit, you know, why is this working better or not? So having that, that digitization of the flow with the feature of computer vision allows us to extract the value. And industries like agriculture are going I mean, agriculture has been a leader in technology for a while, but now you're really seeing adoption at livestock and row crop with drone technology. It's a very rich image environment, medical space, medical space for computer vision in 2022 to 2028, is estimated to be billions of dollars just with medical imaging. And that's not that's not the the total addressable market for the hardware, it's just the imaging piece. So we see we see a lot of growth in sectors that are going through this digital transformation that are adopting technologies that are now getting to the point where they can get pushed down into the masses instead of just the top five companies in the world. Grant Excellent, it seems to you part of your comment earlier made me think about process optimization for organizations, and the ability to extract processes, you're familiar with process mining, right? The ability to extract, you know, out of logs of these organizations and doing something like that where you can produce this visual representation of that, and then building models against that, to optimize your process might be an interesting use case. Yeah, that's fascinating. Carlos That's a really good point, right? Because that's, that's a different portion of AI that can be applied to like just log analysis, that then would allow you to go back and Okay, now that we have the process mind, where can we improve along the process? Grant Yeah, yeah. Amazing. So many uses and use cases around around this CV area, for sure. So let's say that someone listening to this wanted to learn more about it, where would they go? How would they? How would they find more about your organization? Carlos You can find us everywhere, right? We have a website, plainsight.ai. We're all over LinkedIn, we have Twitter, we're on Reddit, we have a Medium blog, there's a Slack channel where we geek out around computer vision use cases and how we can improve the world through computer vision. We're really we're really out there and feel free if you have questions come reach out to us. We have amazing staff that are looking to empower people in AI. So if it's through just just a question around how does this thing work, we'd love to talk to you if it's Hey, we're kind of stuck in our journey. We need some help reach out to us we can help you. Grant That's awesome. Carlos I can't thank you enough for reaching out to me and for a listening to click AI radio, but also for reaching out and sharing what it is you are you and your organization are bringing to the market think you're solving some awesome problems. Carlos Thanks a lot, Grant. Appreciate it. always appreciated talking about computer vision and AI and thank you to you and your listeners and really appreciate what you're doing to the AI space. Grant Alright, thanks again, Carlos. And again, everybody. Thanks for joining and until next time, go get some computer vision from Plainsight.
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CAIR 53: Benefits of AI for Business
11/08/2021
CAIR 53: Benefits of AI for Business
What are some of the ways AI can benefit your business? So with some of the current talent shortage is going on currently in the US the challenges for businesses to find employees or employees are going to be best for your organization. He got me thinking about what are ways in which I can ask AI Please make my job easier, right? What are some ways that I could make better decisions, whether it's finding the right employees, or whether it's building my business with the right business partners? I stepped back and said, Wait a minute, what are the benefits of AI for business? There's many hype out there for sure. Let's look at a few of these. Alright, so one of these is around efficiency and productivity gains, for sure. Right. That's certainly where we're looking for the benefits of improved operational efficiencies for the organization. There's a case study that I saw, this was from [email protected], they were actually talking about, about an AI restaurant, excuse me about an AI driven restaurant. And in this restaurant, they had experienced some slow service times in their drive thru. Also, when people came into the lobby service was slow, there's a high rate of employee turnover. There's all the human aspects of that, certainly in terms of being a great leader. But that aside, they looked at AI to see if they could identify some inefficient operational areas, what came out of it was, the AI helped them improve the speed of their service by 21%, during rush hours, right, that's, that's a really decent improvement. The other was, they improve the efficiency of their kitchen by 53% 53%. So the amount of time it took to actually get the order in, get get food, turn around, get things cleaned up, get food prep, that that sort of stuff. And then of course, their sales, they said increased exponentially as well. Alright, so looking for opportunities to minimize your costs as well as to perform improvements in your operational efficiencies. That's certainly one of the areas for productivity gains. So that's benefit number one or a benefit, another benefit to consider, which is fairly similar to this, but it's all around improving the rate at which you do business, right, the speed of your business, perhaps one of the things that we found in this area is that it's key to focus your AI questioning on specific scenarios of your business. So the idea is rather than trying to, you know, eat the entire elephant, so to speak, metamorph metamorphic Lee is I don't, that's not even a word. Anyway, rather than trying to eat the entire darn elephant, adjusting the AI models based on where you're focusing is critical. So create smaller AI models focused on a certain business scenario. Alright, number three, new capabilities and model expansion. And of course, you know, when you think about AI, sometimes, right? That's when we tend to think of other things like, oh, Elon Musk, or, you know, what they're doing with Tesla, or you know, the autonomous cars, all that sort of stuff. Certainly, there's those models out there, for sure, where new business models being created because of AI. But for for most of us, as we're getting started with AI, that's, that's kind of a step beyond where we typically see see organizations go for typically, you'll tend to start with an efficiency gain, you know, sales, improvement, gain some some things like that, then as you grow, then new opportunities for capabilities start to emerge. Alright, here's another one. That's kind of interesting. It has to do with better customer service so AI can benefit in those areas as well. There's an example that I love on this one is we've all seen you've probably seen nor Domino's Pizza, they are monitoring so when you call and say, hey, I want a pizza. They've got some AI listening and they're trying to figure out hey, is that granted Oh, that's grant on the phone at that Larson home, well then order that guy some some sinister pics right or, or upscale, you know upsell him on that right? So there they eyes listening, it's determining who's on the phone, and then prompting their order takers to customize coupons based on who it is they're talking to. So, quote unquote, better customer service that might be one example. All right, here's another the another benefit is around monitoring of your business and how to improve that. Lots of times what we found in this area is, this requires the AI model to be running somewhere, there's kind of two approaches to think about AI models, there's, there's the approach that says, hey, just give me some of the insights of what you see looking backwards. And then there's also the aspect of using AI in the course of doing your work. And this permits AI monitoring, right? So here's the idea, right? It's as perhaps, as you're going through a particular sale, while you're in the act of doing the sale, the AI model is running somewhere. And it's queried, right? It might be out on Amazon, or Google Cloud or Azure. In any event, it's running out there. And it's watching those business activities. And it's giving you some quote unquote, real time insights or feedback like, hey, the probabilities of this being a good client for you, has dropped dramatically, right? Or perhaps this is, probabilities are high for good one. Alright, so improved monitoring certainly is a key a key area, and it takes a little growth to get to that point, when you've actually got the AI models out there running, you don't have to wait for that to start getting the benefits. If you back up, you can start getting the analytics much sooner to put yourself in a position so you can turn on the monitoring. There's another one here another benefit tends to be around reducing errors that people make that you know, I guess what I'd say here is, this is a key reminder, I think that one of the benefits of AI really is I think we should view it as augmented intelligence, it's, it needs to be looked at as, as something that causes you to think or rethink what you might currently be doing. And sometimes the reduction in human error comes because the AI saw something that causes you to rethink your processes, and then you make changes. And sometimes many times those changes are beyond what the AI saw. But the AI SIRs or served in that scenario is a trigger or an instigator of the change. So in that sense, it can help catch human error, but should always challenge it, right. And so we want the AI to inform us and say, Oh, here's things that our brain couldn't see. But sometimes, you know, doesn't mean the AI is always right. So we wanted to augment your intelligence for sure. Alright, here's the, the one that I sort of started with was around talent and Talent Management and, and, you know, using AI to gauge things like employee sentiment, although I worry about the whole big brother thing, right? Don't really want that. But to monitor the sentiment for sure. I'm not necessarily talking about employee productivity or things like that. Did they log on to their computer the right time? I'm not looking at that, but the way in which they interact or talk or think about things right, or, or to monitor evaluate the the nature of the behavior of your business partners, right? Do I have the right business ecosystem in place? And are these in fact going to be the right business partners for me using AI to augment my talent management, both internal as well as to those external organizations as well? So AI can be used to leverage those kinds of things as well. I've been interested to know what are the highest value areas for you, you can check out click at click AI or radio.com and subscribe and let me know what you think, everybody thanks again for joining and until next time, plan out your business AI benefits. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com Now.
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CAIR 52: Finding Your Best Leads With AI
11/03/2021
CAIR 52: Finding Your Best Leads With AI
In this episode, we take a look at curating those leads which come into your business using AI. Is it possible to underestimate the value of a quality customer in your pipeline, we all have experienced what it means to bring a customer into your business, which later we are kicking ourselves saying, oh, man, I wish you didn't have that customer. Well, can AI do anything for us? Right to lead or not to lead? Right? That's the question to ask AI. Can you help us with this AI? Well, as you know, today, there are multiple AI tools out there which provide insights on qualified leads. Lots of times are looking at things like recency Right? Like how many leads, you know, came in today or yesterday? Or they're looking at frequency? How often did the leads actually touch our organization? Right? Was it through some phone interaction? Or did they click on our sights? Or what did that look like? There's easy to action scores, that of course, you want to try to get in front of your sales teams. And of course, the goal is to leverage that info so that the outcome then becomes realized, right, and it turns into a valuable kind of customer. Now, one of the things that we want to do is we want to connect to a variety of systems downstream. So one of the challenges around lead management and lead AI is you need to be able to organize the information from the earliest touchpoints and identification of who the person is, and follow their lifecycle all the way through to the realization of the income, or the revenue, I should say, coming into the business, or the rejection of it, or the later reclamation of that in the form of a of a refund. So number one, we want to think about how do we connect all of that data together and tell that story, really looking for a series of breadcrumbs, if you will, that ultimately can knit and tie that together. And for a lot of businesses today is you know that this is found in a lot of different systems, right from things like HubSpot, or you know, Pendo, or what have you, right that the data is all over the place. But number one, you want to think about fit, right? You want to think about who are your leads, right? And how do they match what your ideal customer profile looks like? Do you even know what that is? Have you described that perhaps some refer to that as I see p. The world needs another acronym, right ICP. But nevertheless, this is a critical one, what's your ideal customer profile? What do they fit? What does it look like? Can I describe that, and in order to apply AI to leads, it helps for me to see that now, quite frankly, using AI to help describe that is actually very common practice. So if you think well, I don't really have my ICP defined. That's all right, run a series of AI analyses on the full lifecycle of your leads. And in time, the AI will begin to discover what that looks like for you. So you don't have to have that first. In fact, the act of preparing AI for leads can help you to develop that. Certainly you want to understand, though, what's the leads activity? What are they doing? What's their ultimate intent? And of course, how often do they actually touch and interact with it with the organization? It turns out that in some cases, it's actually more valuable to reduce the number of leads in terms of, you know, all those we're working with in the organization and actually increasing our sales. So if I could reduce my leads, let's say in half, but of that remaining half, I have very high close rate, then my cost of goods sold starts to drop dramatically, and so becomes really valuable to the organization. So it's all about finding revenue, obviously, revenue specifically that's untapped in the organization. This is one of those efficiencies. Laser optimization plays that we do on a business, right? It's not necessarily saying, Oh, we're going to go after a new business model or changing this or that this is looking within your current pipeline of the kinds of leads that come through, how can we optimize our behavior so that we return the best possible dollar to the organization. Alright, so, in general, that's the model. But rather than a generic model, I wanted to introduce five or six different scenarios around leads to consider. Alright, so one of these is around product, profitability impact. And I'll come back to these here in a minute, there's lead or customer segmentation. Another or third scenario is around date or time of sale. There's refund impacts around leads, there's demographics, obviously, for leads, and then there's what we like to call destructive behavior. All right, so let me just to maybe peel the onion back, go down one more layer on each of these. So on this first one on product profitability impact, the real question is, what are the conditions that surround a lead that produces the higher profitability? And of course, as you know, a lot of groups are focusing on the sales itself, which is obviously good. But quite frankly, having your AI pivot on your profitability is a key question to ask your AI solution. So when you're working on leads, build that connective tissue to the ultimate products. And then not only that, but the profitability of those that starts to pay you back very quickly, in terms of any investments that you do with AI actually very strong impact. Here's another one that pays back your AI efforts. It's around lead lead segmentation, right. And of course, it's finding those segments that drive towards higher sales growth, and of course, higher profitable growth and the ability to segment that, obviously, your benefits certainly marketing activities, pricing opportunities, as well as value delivered to that lead, who becomes a customer. Alright, so having the AI work on that highly valuable. third scenario for AI with leads, of course, you know, when the lead progresses to the point of sale, or for every touch point leading up to that sale, understanding the insights of those touch points, the timing, the areas of interest, etc, that leads some some very insightful AI analysis as well as predictive behavior. That certainly tipped you off as a business owner of when to proceed or when to stop pursuit, the sooner we can stop the pursuit of something that by prediction says, this will waste your time, then certainly the better the better than it is. I had an experience one time with an organization that was trying to sell something. And at one point, I was not getting the cycles. And the salesperson looked at me and said, I'm going to start to I'm going to stop talking to you. I said, Yeah, it's probably a good idea. So he figured out, yeah, I wasn't going to be the right one. So the better you know, the sooner Of course, we can find these, the better. So date, time of sale, meaning all the touch points throughout the lifecycle of the lead. Those scenarios, obviously, very critical. Ask your AI to look into that. Number three places to put the AI for leads is around, you know, refund impact, of course, is when your your lead turns into a sale, of course, that ultimately then turns into a refund. And it's certainly critical to understand what those look like and how we can get away from and move away from those sorts of situations. The fourth, or excuse me, the fifth scenarios around demographics. So lead demographics. Now, sometimes this can also be aligned with lead segmentation, but not all segmentations are demographic based. And so that's why we break it out, because we see situations where organizations actually treat that as a separate segmentation. So within some segmentation that they'll have to then do further demographics work. Of course, it permits you to focus your messaging and your marketing into sub markets, where things have historically been lucrative or for which you have a high predictive probability. So applying leads to this sub area around demographics for your leads, very, very powerful. Alright, and then the last one I mentioned here, is around what we call destructive behavior. And I recall early on when we first started applying AI for companies and we got to a point where we said to one of our clients, oh, and by the way, look, we've been able to prove out here with high probability you need to stop having salesperson x with with product why in this particular scenario, the client went home Wow Okay, hadn't even seen that and understanding those kinds of destructive behaviors things to stop. So, in the same vein doing that with leads is also critical which is stop going after certain kinds of leads as early as possible and how asking the AI tell me what are those conditions or situations in which the lead produces destructive or bad behavior and let the AI find those bad situations so that actually becomes a critical thing to understand obviously, alright, so as you know, there's a range of AI solutions out there today certainly to help you with leads now whether use that we know one of them or you use click AI the real trick is to get control of the front end of your business and and certainly qualify with AI your intake process, obviously reducing you know, the less qualified leads the earlier than certainly it's better for the business. Okay, everybody. Thanks for joining. Until next time, get some AI for your leads. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your free ebook, visit ClickAIRadio.com Now.
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CAIR 51: Does Elon Musk REALLY Use AI To MANAGE HIS TIME ??
10/21/2021
CAIR 51: Does Elon Musk REALLY Use AI To MANAGE HIS TIME ??
So how does Elon Musk manage his time? Is it AI? Come join us and find out. Hi everybody, welcome to another episode of ClickAI Radio. So Mr. Musk, how do you do it? Calling out Mr. Musk. All right. So of course we've I'm sure all seen the video where it talks about how he manages his time, he manages his time, apparently using timeboxing. And on some of these reports that I've seen, he says he spends 80% of his time doing engineering design work. That's pretty amazing. And that, some have said that he manages time down to five minutes slots, holy chicken soup, that's pretty tight. So what it means is that he plans out his whole day on five minute increments, that's quite the level of planning. I don't know for sure if that's what he does, but time boxing. So apparently what you do with time boxing is, as you plan it out, you put it on a whiteboard or a note paper, whatever. And then of course, you fill out the time that you think it's gonna take to get that done. All right. Now, of course, there's some fallacies and problems with this right? One of those is, as humans, we seem to overestimate. We're overly optimistic, I should say in terms of how long things will take, we think it might take 10 minutes to do something. In reality, maybe it's 20 minutes, right? And of course, there have been studies that talk about people tend to choose the best case scenarios, right? When we're, when we're allocating our estimates for time. This, of course, makes timeboxing really difficult, which would look like if you had a piece of paper, a series of time slots at some increment. Now, apparently, five minutes for Mr. Musk, I would do more like 15 minutes. But hey, who knows? In any event, so when you come up with those, one of the challenges is, how can I improve my accuracy for that? Turns out, there's some tools out there today to sort of help you do this toggl, t-o-g-g-l is one of those tools to help you track your time and see how things are gone. This can of course be painful to do. I listened to one guy, he has a technique where he asks you to go through and describe everything you did for two for two weeks. So every day you write down on a piece of paper for two weeks what you did. And then at the end, he calls it a time study at the end of the two weeks, and you really kind of have a sense of where you're spending your time. And I've talked to multiple people that have done this. And they all complain about it saying what a total pain. And yet how revelatory and insightful it is when you start to see some of the areas that they're spending their time that actually was, was lost to them, right? lost productivity and things that are meaningful and useful. Of course, one of the big objections to time boxing, which says, I'm going to plan out my day on some sort of increment and for each increment, here's here's a box of what I'm doing. One of the objections is around interruptions, right? So let's say you had planned out your entire day for that. Now, how do you deal with the interruptions? I know some people to deal with that. They'll create two columns. They'll have one column that says, here's the my original plan. And then and then they'll have another column, which is the revised plan, right, which Well, here's really what happened, right? thought I was going to be doing this activity of this task. Turns out, I did something else because I was interrupted. I think it was Dwight Eisenhower. That said, planning is everything but plans are nothing. Well, so of course the bottom line is we need to be able to pivot in order to adapt and adjust certainly. And of course, we need to avoid over scheduling too because some also have said that the more you try to do, the less you will accomplish. I think there's something to that. If I context switch too much, man on a five minute increment. Wow, Mr. Musk, if that's true, hats off to you. Five minutes in That's that's that's pretty tough to context switch constantly like that. I think that might be some overscheduling. Who knows? Well, that's why he's where he is, I suppose. Others have said that the way in which they plan, they'll organize it based on the intent for their business. So they'll plan tasks and activities in the morning, that have to do with money generation and revenue generation activities, when they're the most fresh. Those are the areas they want to put most of their intellectual capacity to. And so they'll do those types of time boxed activities in the morning. And in the afternoon, it's more cost management expenses, things on the cost side of the balance sheet, that's interesting technique, then I started to look into AI for time management, you've probably seen there's an app out there called timely think it's from a company called memory AI Anyway, you can download, I think the way it works is you download it onto your Mac or your Windows computer, you start connecting it to your Google calendar or other calendars. And over time, you start training the AI to start recognizing how you're spending your time, and you ultimately are teaching the AI model, something about your work schedule and the way your time is being spent. Now, why would I even talk about time management? What does that have to do? Well, one of the things I've noticed is that, given the increased demand, of course, on SMB owners, finding ways, obviously, to optimize our schedules is certainly important. But the real reason is, many view activities to transform their business as too much of a stretch, right? Because we're so busy running around just keeping the lights on as a small to medium business owner, who can think about adding more activities to our days. So you know, things like, hey, maybe I can improve my decision making by looking at more analytics, right? Or, hey, I could spend some extra time making changes to my business processes through AI insights. Yeah, sounds interesting, but also sounds like, hey, you're being told to take your vitamins. And who wants to do that, right? That's not too exciting. So what you really need to do my experience with his bins is we need to find what's the real business cause, or the motivation to do something like that, right? So sometimes it might be competitive pressure, or it might be a business model threat, right? Or might be growth goals or, or even cost pressures. And when something like one of those is understood first, then finding the time by doing some kind of time analysis helps us to free up the cycles to address this. So I kind of have to find the why right? Why is it that I would do this? What is it that's pushing me, right? And lots of times as humans will move away from pain faster than will move towards a goal. So if you can find, where's my pain point, my business? What is it that would drive me and give me the motivation to make this kind of adjustment, then I can start finding the business context, where I'll start making the changes then to leverage new techniques such as putting AI into your business. I was talking with a large retail organization not too long ago, they said that, before the covid 19 pandemic, they had discussed providing curbside service, right. But at the time, the estimates in the organization, they said it would take about two years to roll that out. And then when the pandemic hit, they were able to roll it out in four weeks, right? So suddenly, obviously, there's this, there's this pain, right? There's this pressure, we have to do business differently, the context has shifted. So finding the motivation, then allowed them to find the time and then suddenly, a lot of the red tape and other things move out of the way. So find your motivation for change as a business owner, right? Then find the time to pursue the change. Those are the precursors for most organizations to pursue an AI strategy. Now many times of course, like I said, we move away from pain more quickly. So where does your business hurt? And then let's get AI on the job. All right, everybody. Thanks for joining and until next time, find your motivating factors to set aside the time to apply AI in your business. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your FREE eBook visit ClickAIRadio.com now.
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CAIR 50: The Skills Gap Really AFFECTING YOUR Business !
10/19/2021
CAIR 50: The Skills Gap Really AFFECTING YOUR Business !
In this episode, we take a look at the skills gap that's really affecting your business. Welcome everybody to another episode of ClickAI Radio. All right. So in overcoming the lack of skills in your business, now I'm going to start with, with the focus on AI itself, right, and what that looks like. And I'm going to pull here from certainly my own experiences, but also this is a report I saw from Deloitte, they had they'd said that, hey, they found that those companies that are seasoned with AI skills, they didn't feel they had a big skills gap. Oh, that makes sense. Right. The other thing they pointed out, though, is that the companies that are doing a lot of AI right now are really focusing more on transformational projects than on cost reduction. So from their perspective, hey, when you're getting started, you're often looking at cost reduction as a way to leverage AI. Hmm, I don't know my experience, I've found that it's been more around sales and say, of course, in the supply chain area, there certainly cost reduction there. So all right, that makes some sense. It also said that they broke it into three categories. There were those companies that were seasoned with AI, then the other categories are skilled with AI, and then the other word, the starters, and said that the seasoned ones are of course relying on their own internal skilled resources, had stair season, I guess, by definition, whereas the starters, were leaning more on other companies, right, they're outsourcing some of the AI itself. A couple other points here from this report. So they indicated that two thirds of the seasoned adopters are currently training their developers to create new AI solutions. They're providing more training for more of their employees to do AI work. So rather than leaning away from it, they're actually leaning more into it, because of some of the benefits that they're pulling from it. In another report, this comes from the hill, they said, like there's concerned about AI, an AI workforce, specifically shortage, an AI workforce shortage in the United States becoming a top national security priority. And there are some calls for some legislative action. They're trying to compete with other countries like China and others. But you know, some see little data on the actual AI labor market dynamics, is it really, is there really a workforce shortage? And if so, what does that look like? Now? How do you even quantify that, so you have to back up and think about the skills of AI itself. Now, given that my intent here is true to target and speak with the small to medium business owner, for the most parts, I'm never gonna say go build your own data science team, it's too expensive, as well as you're not going to get the ROI on it. As we all know, we saw that report from MIT last year. That said, Only 10% of companies that are building out their own teams like this are actually achieving achieving the financial results. So we're not we're not going to focus on that, rather, I'm going to target let's go after another approach. There's certainly a shortage of AI skills in the US, right? But hiring your own team to do that isn't going to be the best way. So if you use an AI service and rent the capabilities to get the insights at a fraction of the cost, then if there's not an AI skills gap from your, from your organization, excuse me, then what really is the gap that you're facing? what's what's missing, in terms of you achieving the effects. So the benefits of AI? Well, there is still a skills gap. And the skills gap, though, comes in areas that are not too strange sounding to us. In other words, it's not going to be hey, can your can your particular business analyst deal with, you know, logistic regression algorithms? No, no, no, that that's for the AI people to figure out but as a small to medium business owner, you don't worry about that part. But there are some skill sets that you do need to have or strengthen in your team in order To be effective with leveraging the effects of AI, so I'm going to pull from this report this comes from, from go scale, excuse me, yeah, go go skills excuse me, they they reported that there were three hard skills lacking in recent graduates. This is interesting, right? And it's stuff you already know, right? It's writing proficiency, public speaking, and data analysis, let's apply this to AI, right. So as a small to medium business owner, you want to play AI, you don't need to go deep on all the AI skills. But what you do need to go deep on is your ability to leverage those insights into your business. And that's where you need to spend the time building up your team. Let's look at writing proficiency, Well, certainly AI does a great job at identifying those things that our our brains can't see. So it's also critical that we describe meaning we can write down what the business problems are, and what the challenges are. So writing proficiency does affect the ability to properly point to and use and therefore adopt AI in your small to medium business, public speaking Well, this, of course, dramatically affects your ability to communicate. But specifically, the ability to communicate the transformation, the iterative transformation that your business goes through, when you apply AI, you know, you never apply AI, once you apply it, make a couple small steps, and then apply it again, you do it incrementally, but you also need to be able to communicate, what's the journey that we're on? Alright, so public speaking, whether that's external to your customers, where they're seeing the impacts of this, or internally, the ability to speak is critical. And then third, here was data analysis. And of course, you know, the ability to create insights on your data, use an Excel or whatever other tools, tableau, etc. Those are certainly critical. But in this case, they're critical to help point out that there's a case for AI. Let me let me illustrate that. I was talking with a business executive actually, just last week, who made a statement that although his engineers could do data analysis, they had that skills to use the you know, the various tools to do that. They could not estimate their supplier forecasting, because the data was spread out across so many systems and was so many levels deep, that just the the, you know, analytics tools couldn't actually give them the insights they needed. This is a great place for AI to step in, right. And they were wise to recognize the limits of the data analysis and said, we're not solving the problem, right, the data spread out too much. And so they saw the opportunity for AI to help out. So yes, be skilled the data analysis, but also be skilled at knowing what its limits are. Right. So those are three hard skills that your teams today already have, but course need to strengthen and bone up on. Let's look at some soft skills that was reported out here by this ghost skills report. The five most lacking soft skills in employees they pointed out was number one, critical thinking and problem solving. Number two, attention to detail three communication for leadership and five teamwork. All right, so let's let's just pull these apart here real quick. So critical thinking and problem solving, obviously selecting the right use case to apply AI to solve business problems. That is critical fact that thinking is so critical that we've seen multiple failed AI use cases in the market, right? And of course, it gives a black eye on AI, right? It's like Oh, you're applying AI how you're doing what with it? No. So stay is a small to medium business person stay in the guardrails of sales, use cases and supply chain use cases, right? Look in those areas. And don't go outside of that elite, at least for now. Alright, as AI matures and grows. And as you feel like hey, you've got a handle on this, then certainly go wider. But for now just focus on in those two areas. Number two, the attention to detail. Well, I'm an admitted nerd, and it's so it's easy for some of us to pay attention to detail. But this in fact, becomes our weakness at times, right? We, we can't always see the business problem. So it's critical to help your people certainly have attention to detail, but also be able to step back and look at the context of that. And then this third bucket here communication, leadership, teamwork, you'll need to apply AI transformation as a team, alright, it's because it will affect business processes as you transform your business getting the insights from AI. So it turns out that your organization already has the fundamental skills for AI, not to build your own data science team, but rather to apply the resources. But what it means though, is that you need to strengthen those current skills so that you can be more successful at applying. All right everybody. Thanks for joining and until next time upskill your team to leverage AI services to transform your business. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your FREE eBook visit ClickAIRadio.com now.
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CAIR 49: Is Your AI Hammer Looking for a Nail ??
10/16/2021
CAIR 49: Is Your AI Hammer Looking for a Nail ??
In this episode, we take a look at the AI hammer that's looking for a nail. Hey, welcome everybody to another episode of ClickAI Radio. So I was talking with a group of technical people recently. And they talked about a very cool solution that they prepared. So I asked this question I said, so which part of your business will this benefit? And they said, well, we're still trying to figure that out. I said, Oh, you've got a solution looking for a problem. Is that exactly. I said, Well, you know, if you're not careful, AI can turn out to be the same thing, right? One of the biggest mistakes you can do with AI, in fact, this happens quite often is it's the tendency to create AI solutions. without sufficient understanding of the business problem. Everyone gets excited and enamored about the technology, well, maybe not everyone, but some do. And so it turns out that a crisp definition or description of your business problem is of course critical. However, as you know, with AI, you can, you can do a bit of both, in fact, that encouraged both, it kind of looks like this. So start by building your AI solution. And what you do, the reason you do that is you run it against some of your data. And it gives you a sense, without any sort of tutoring or guidance on your part, it gives us a sense of identifying what it can see, right, and what it does is, it lets you understand the potential areas or problems that the AI can start providing answers to. So with those kind of insights, initial insights, you can go back to the drawing board and rethink the kinds of problems which may be addressable with the kind of data that you have, that's actually really critical to do early on. Some groups will spend a lot of time doing lots of data curation, cleaning stuff up over long periods of time. And the whole time, the other hand is saying, Oh, these are the problems, we want to go solve with it. And then the two don't meet, right, you don't have the kind of information that's even needed, that AI would need to dress it. So what you're really trying to do is an interactive iterative, give and take process, as a way to think about it. Now, I've never seen a situation where the first time the AI solution was created, that it was ready to be used by the business. So you should get that out of your mind. Rather adjust your thinking, to consider discovering what the possible problems are, that can be solved with AI by looking at your data, then go back, evaluate the business problems, and continue to iterate and fine tune that right, you can certainly grow and build on your data set after you do that, but save a lot of time by doing that. All right, well, let's talk about what actually is a more significant and critical way to look at this. So in reality, as you know, most of our businesses have many existing systems, right? And our business information, of course, is spread across the systems with lots of redundant data. Well, we of course, rely on our teams and our brains, obviously, to logically connect the information together on these systems, so that we can have the kind of information that we as humans need in order to make decisions. Now, when we use AI, we want to think about recreating that kind of experience. And you can go through the process, certainly of saying let's integrate all of our systems together. But that can be a real challenge. So for example, let's say that you have three systems. This will be a little bit oversimplified, but let's say you have one system for leads and lead management. Then you have another system for ads and ad campaigns to those leads. And maybe you have a third system that's used for closing sales and servicing. All right, a bit oversimplified, but it's sufficient for the example. So it turns out as you know that your customer Numbers journey unknown to them touches each of those systems. And of course, in many cases, those individual systems provide analytics and insights in their respective rights, which is cool and helpful. But your brain ties that all together into an overarching customer journey or customer lifecycle. So this is where AI can work wonders. So even though these systems may not be connected, or even integrated, using AI, along with some data management, the AI can look across that entire data set from those three systems as one data set, right and view the whole customer lifecycle. So then with that the the AI can identify what are the probabilities that a certain lead will translate into a closed sale, even though your own systems aren't integrated to sport that AI can actually do that work and give you those insights. So you don't need to do that integration in order to make that happen. So I encourage you to focus less on getting all those systems connected, or even transfer, you know, transforming or moving your data to one system that does it all. Certainly, that's good. And there's some benefits of doing that. But the key is, don't focus on getting all those connected, but rather focus more on understanding what the predictive golden nuggets are that are already hiding in plain sight across your integrated data, not necessarily integrated systems, but you integrated data and let the I see that. It turns out that this is a nail that the AI hammer can use. Alright, thanks for joining until next time, everybody. Get a holistic view of your disconnected systems with AI. Thank you for joining Grant on ClickAI Radio. Don't forget to subscribe and leave feedback. And remember to download your FREE eBook visit ClickAIRadio.com now.
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