Tech Talks Daily

If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change? Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways. Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses. Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn't just about buzzwords. We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make. Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn't, and how businesses can maximize their investments. Whether you're a business leader, IT professional, or simply curious about technology's role in our lives, you'll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas. New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

3418: Scaling IoT Security with Real Time Visibility at Wireless Logic 09/12/2025

3418: Scaling IoT Security with Real Time Visibility at Wireless Logic Here’s the thing. Connecting thousands of devices is the easy part. Keeping them resilient and secure as you grow is where the real work lives. In this episode, I sit down with Iain Davidson, Senior Product Manager at Wireless Logic, to unpack what happens when connectivity, security, and operations meet in the real world. Wireless Logic connects a new IoT device every 18 seconds, with more than 18 million active subscriptions across 165 countries and partnerships with over 750 mobile networks. That reach brings hard lessons about where projects stall, where breaches begin, and how to build systems that can take a hit without taking your business offline. Iain lays out a simple idea that more teams need to hear. Resilience and security have to scale at the same pace as your device rollouts. He explains why fallback connectivity, private networking, and an IoT-optimised mobile core such as Conexa set the ground rules, but the real differentiator is visibility. If you cannot see what your fleet is doing in near real time, you are guessing. We talk through Wireless Logic’s agentless anomaly and threat detection that runs in the mobile core, creating behavioural baselines and flagging malware events, backdoors, and suspicious traffic before small issues become outages. It is an early warning layer for fleets that often live beyond the traditional IT perimeter. We also get honest about risk. Iain shares why one in three breaches now involve an IoT device and why detection can still take months. Ransomware demands grab headlines, but the quiet damage shows up in recovery costs, truck rolls, and trust lost with customers. Then there is compliance. With new rules tightening in Europe and beyond, scaling without protection does not only invite attackers. It can keep you out of the market. Iain’s message is clear. Bake security in from day one through defend, detect, react practices, supply chain checks, secure boot and firmware integrity, OTA updates, and the discipline to rehearse incident playbooks so people know what to do when alarms sound. What if you already shipped devices without all of that in place? We cover that too. From migrating SIMs into secure private networks to quarantining suspect endpoints and turning on core-level detection without adding agents, there are practical ways to raise your posture without ripping and replacing hardware. Automation helps, especially at global scale, but people still make the judgment calls. Train your teams, run simulations, and give both humans and digital systems clear rules for when to block, when to escalate, and when to restore from backup. I left this conversation with a simple takeaway. Growth is only real if it is durable. If you are rolling out EV chargers, medical devices, cameras, industrial sensors, or anything that talks to the network, this episode gives you a working playbook for scaling with confidence. Connect with Iain on LinkedIn, explore the IoT security resources at WirelessLogic.com, or reach the team at . ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/38140335

3417: Inflection AI and the Rise of Contextual Intelligence 09/11/2025

3417: Inflection AI and the Rise of Contextual Intelligence Here's the thing. Most enterprise AI pitches talk about scale and speed. Fewer talk about trust, tone, and culture. In this conversation with Inflection AI's Amit Manjhi and Shruti Prakash, I explore a different path for enterprise AI, one that combines emotional intelligence with analytical horsepower, enabling teams to ask more informed questions of their data and receive answers that are grounded in context. Amit's story sets the pace. He is a three-time founder, a YC alum, and a CS PhD who has solved complex problems across mobile, ad tech, and data. Shruti complements that arc with a product lens shaped by real operational trenches, from clean rooms to grocery retail analytics. Together, they built BoostKPI during the pandemic, transforming natural language into actionable insights, and then joined Inflection AI to help refocus the company on achieving enterprise outcomes. Their shared north star is simple to say yet tricky to execute. Make data analysis conversational, accurate, and emotionally aware so people actually use it. We unpack Inflection's shift from Pi's consumer roots to privacy-first enterprise tools. That history matters because it gives the team a head start on EQ. When you combine a deep well of human-to-AI conversations with modern LLMs, you get systems that explain, probe, and adapt rather than dump charts and call it a day. Shruti breaks down what dialogue with data looks like in practice. Think back-and-forth exchanges that move from "what happened" to "why it happened," then on to "where else this pattern appears" and "what to do next," all grounded in an organization's language and values. Amit takes us under the hood on deployment choices and ownership. If a customer wants on-prem or VPC, they get it. If they're going to fine-tune models to their vernacular, they can. The model, the insights, and the guardrails remain in the customer's control. I enjoyed the honesty around adoption. Chasing AGI makes headlines, but it rarely helps a merchandising manager spot an early drop in lifetime value or a CX lead understand churn risk before quarter end. The duo keeps the conversation grounded in everyday questions that drive numbers and reduce meetings. They describe a path where EQ and IQ come together to form what Shruti calls contextual intelligence, and where brands can trust AI agents to assist without losing ownership or voice. If you care about making data useful to more people, and you want AI that sounds like your company rather than a generic assistant, this one is for you. We cover startup lessons, the reality of cofounding as a couple during lockdowns, and how Inflection is working with large enterprises to bring conversational analysis to real workloads. It is a grounded look at where enterprise AI is heading, and a timely reminder that technology should elevate humans, not replace them. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/38048805

3416: DEUNA: From One-Click Checkout to Intelligent Payments Infrastructure 09/10/2025

3416: DEUNA: From One-Click Checkout to Intelligent Payments Infrastructure Here’s the thing. Payments only look simple from the outside. In this Tech Talks Daily episode, I sit down with Roberto “Reks” Kafati, CEO and co-founder of DEUNA, to unpack how a scrappy one-click checkout idea grew into an intelligent payments infrastructure that now touches a large slice of Mexico’s online economy. Reks explains why Latin America’s high decline rates aren’t just an inconvenience but a growth killer, and how DEUNA’s early focus on orchestration and checkout opened the door to something bigger. When a region routinely sees more than four out of ten online transactions knocked back, the bar for reliability sits in a different place. That practical problem set the stage for what came next. Athia, Real-Time Decisions, and 638 Signals per Transaction DEUNA’s pivot point came when merchants asked a fair question. With all this payment data flying through the system, what should we do with it? The answer is Athia, DEUNA’s AI-powered layer that watches every transaction and feeds merchants real-time insight, routing choices, and suggested actions. It is not another dashboard you promise to check and then ignore by Friday. It is a reasoning engine that sits on top of 638 data points per transaction and turns mess into movement. That is how you recover revenue without punishing good customers with extra friction, how you avoid surprise fees from networks, and how you protect recurring revenue when a processor wobbles. Reks walks us through results that speak plainly. Ramped merchants saw conversion lift from the original one-click experience. The infrastructure tier recovers meaningful GMV and trims fees. Enterprise clients report double-digit ROI and stick around for the compounding effect. Building Through Adversity and Betting on the Right Layer What resonated most was the human story behind the metrics. DEUNA was born in the first months of the pandemic, shaped by the shock that hit real-world businesses when revenue fell off a cliff and marketplaces became a lifeline with strings attached. Reks shares an unvarnished look at a tough 2023, the kind of year founders rarely talk about on record. Revenues dipped, deals went sideways, life got complicated. The team chose resilience and doubled down on a two-year vision. That bet is paying off. Over the past twenty-four months the company has grown at a pace that would bend a chart, and the focus has shifted from commoditizing orchestration to productizing intelligence. Put simply, earn trust at checkout, then make the data work for the merchant in real time. Agentic Commerce, US Expansion, and What Comes Next We also look forward. If chat interfaces begin to mediate more buying decisions, merchants will need infrastructure that can think, not just connect endpoints. That is the territory DEUNA calls intelligent infrastructure, and it is where Athia operates every day. The company is now in active conversations with major US retailers, confident after winning head-to-head enterprise evaluations. Reks frames the opportunity without hype. If you can see acceptance trends by processor, by country, by card type, and act in the moment, you keep customers, protect margins, and avoid death by a thousand false declines. If you cannot, competitors will gladly welcome your frustrated shoppers. If you care about the real mechanics of growth, this conversation is for you. We talk conversion lift, recovered revenue, and the gritty bits of building a payments company that merchants actually rely on. We also talk about the days that test your resolve and the tenth day that reminds you why you started. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/38049755

3415: Secure GenAI for SAP: Syntax Systems CodeGenie on BTP 09/09/2025

3415: Secure GenAI for SAP: Syntax Systems CodeGenie on BTP I sat down with Leo de Araujo, Head of Global Business Innovation at Syntax Systems, to unpack a problem every SAP team knows too well. Years of enhancements and quick fixes leave you with custom code that nobody wants to document, a maze of SharePoint folders, and hard questions whenever S/4HANA comes up. What does this program do. What breaks if we change that field. Do we have three versions of the same thing. Leo’s answer is Syntax AI CodeGenie, an agentic AI solution with a built-in chatbot that finally treats documentation and code understanding as a living part of the system, not an afterthought. Here’s the thing. CodeGenie automates the creation and upkeep of custom code documentation, then lets you ask plain-language questions about function and business value. Instead of hunting through 40-page PDFs, teams can ask, “Do we already upload sales orders from Excel,” or “What depends on this BAdI,” and get an instant explanation. That changes migration planning. You can see what to keep, what to retire, and where standard capabilities or new extensions make more sense, which shortens the path to S/4HANA Cloud and helps you stay on a clean core. We also talk about how this is delivered. CodeGenie runs on SAP Business Technology Platform, connects through standard APIs, and avoids intrusive add-ons. It is compatible with SAP S/4HANA, S/4HANA Cloud Private Edition through RISE with SAP, and on-premises ECC. Security comes first, with tenant isolation for each customer and no custom code shared externally or used for AI model training. The result is a setup that respects enterprise guardrails while still giving developers and architects fast answers. Clean core gets a plain explanation in this episode. Build outside the application with published APIs, keep upgrades predictable, and innovate at the edge where you can move quickly. CodeGenie gives you the visibility to make that real, surfacing what you actually run today and how it ties to outcomes, so you can design a migration roadmap that fits the business rather than guessing from stale documents. Leo also previews the Gen AI Starter Pack, launching September 9. It bundles a managed, model-flexible platform with workshops, use-case ideation, and initial builds, so teams can move from curiosity to working solutions without locking themselves into a single provider. Paired with CodeGenie and Syntax’s development accelerators, the Starter Pack points toward something SAP leaders have wanted for years, a practical way to shift from in-core customizations to clean-core extensions with much less friction. If you are planning S/4HANA, balancing hybrid and multi-cloud realities, or simply tired of tribal knowledge around critical programs, this conversation is for you. We get specific about how CodeGenie works, where it saves time and cost, and how Syntax is shaping a playbook for AI that helps teams deliver results they can trust. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/38112910

3414: Self-Healing Machines and Robotics with Grace Technologies 09/08/2025

3414: Self-Healing Machines and Robotics with Grace Technologies Drew Allen, CEO of Grace Technologies, shares real stories from the floor, the ideas shaping safer plants, and why culture matters more than slogans. Drew’s background stretches from a family line linked to Samuel Morse to teenage years in China to global business development at 3M. That range shows up in how he leads. He listens, he moves fast, and he expects teams to work on things that matter. In his world that means saving electricians from shocks and arc flash while helping manufacturers modernize without losing their soul. Grace started with mechanical and analog products, then took the hard road into fully digital systems. The shift took time and patience. Today their platform brings sensors, AI, and cloud tooling into maintenance and safety. The example that stuck with me is a proximity band for electricians. It lights, beeps, and vibrates as a worker approaches live voltage. At TriCity, that band prevented three near misses in a three month pilot. A fourth incident still ended in a hospital visit and a costly outage because the worker left the band in his car. Another apprentice nearly placed a hand on a live bus bar until the band told him something was wrong. These moments remind you that technology can change a day and a life. Drew’s take on culture is refreshingly direct. Values are not a poster. They are a filter for who you hire. He looks for customer obsession, ownership, curiosity, and candid communication. Then he pairs that with high expectations and real care. Autonomy comes with accountability. Impact matters. If someone does not want to work on meaningful problems, this is not their place. It sounds firm. It also explains why the company keeps earning top workplace recognition while raising the bar on performance. We also talked about Maple Studios, the startup incubator Drew launched in Davenport, Iowa. He sees gaps in the industrial ecosystem. Fewer big exits. Slow adoption cycles. Founders stuck inside large companies. Maple gives them tools, space, and hard feedback so they can iterate faster and build things factories will actually deploy. His advice is simple. Ship, learn, and repeat. Do customer reviews early. Expect a thousand small gotchas. Move through them rather than pretending they will not appear. Looking ahead, Drew expects robotics to accelerate for a very practical reason. Companies cannot find enough people. Dangerous work will be automated. He imagines maintenance tasks shifting toward humanoid robots, with machines designed so robotic agents can service them. He also references GM’s self healing language to point at a coming blend of sensing, prediction, and automated repair. On AI, he shares Satya Nadella’s challenge. Measure productivity and GDP impact rather than hype. The promise is there. The scoreboard will tell the story. If you work in industrial tech, this conversation lands close to home. You will hear how to bring digital tools into legacy environments, how to design for safety from the start, and how to keep teams motivated without losing kindness. You will also catch an open invitation. Drew wants to partner with builders who care about this space. If that is you, reach out to him on LinkedIn or visit graceport.com. And if you are curious about the band that vibrates before a bad day begins, this episode is a good place to start. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37863050

3413: Why Medium-Range Forecasts Could Save Millions: Lessons from Planette AI 09/07/2025

3413: Why Medium-Range Forecasts Could Save Millions: Lessons from Planette AI I spoke with Kalai Ramea at a timely moment. We recorded this conversation during a heatwave in the UK, which made her work at Planette AI feel very real. Kalai calls herself an all-purpose scientist, with a path that runs through California climate policy, Xerox PARC, and now a startup focused on the forecast window that most people ignore. Not tomorrow’s weather. Not far-off climate scenarios. The space in between. Two weeks to two months out, where decisions get made and money is on the line. Kalai explains Planette AI’s idea of scientific AI in plain words. Instead of learning from yesterday’s weather patterns and hoping the future looks the same, their models learn physics from earth system simulations. Ocean meets atmosphere, energy moves, and the model learns those relationships directly. That matters in a warming world where history is a shaky guide. It also shortens time to insight. Traditional models can take weeks to run. If the output arrives after the risky period has passed, it is trivia. tte AI is building for speed and usefulness. The value shows up in places you can picture. Event planners deciding whether to green-light a festival. Airlines shaping schedules and staffing. Farmers choosing when to plant and irrigate. Insurers pricing risk without leaning only on the past. Kalai shared a telling backcast of Bonnaroo in Tennessee, where flooding forced a last-minute cancellation. Their system showed heavy-rain signals weeks ahead. That kind of lead time changes outcomes, budgets, and stress levels. From Jargon To Decisions What I appreciate most about this story is the focus on access. Too many forecasts live in papers that only specialists read. Kalai and team are working to strip away jargon and deliver answers people can act on. Will it rain enough to trigger a payout. Will a heat threshold be crossed. Will the next month bring the kind of wind that matters for grid operations. The delivery matters as much as the math. NetCDF files might work for researchers, but a map, a simple number, or a chat interface is what users reach for when time is short. There is also a financial thread running through this work. Climate risk now shapes crop insurance, carbon programs, and balance sheets. Parametric insurance is growing because it is simple. Set a threshold. If it hits, the policy pays. Better medium-range signals make those products fairer and more useful. Kalai describes Planette AI’s role as a baseline layer others can build on, a kind of AWS for climate intelligence. That framing fits. No single company will build every app in this space. A reliable core makes the rest possible. Kalai’s path ties it all together. Policy taught her how decisions get made. PARC sharpened her instincts for practical AI. PlanetteAI is the result. If you care about planning beyond next week, this episode will give you a new way to think about forecasts and the tools that power them. I will add the blog link Kalai shared in the show notes. In the meantime, if you are in agriculture, travel, energy, or insurance, ask yourself a simple question. What would you change if you had a trustworthy signal three to eight weeks ahead. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37888695

3412: PuppyGraph at the IT Press Tour: Graph Power Without the Pain 09/06/2025

3412: PuppyGraph at the IT Press Tour: Graph Power Without the Pain During the IT Press Tour, I had the pleasure of speaking with Weimo Liu, CEO and co-founder of PuppyGraph, and hearing firsthand how his team is rethinking graph technology for the enterprise. In this episode of Tech Talks Daily, Weimo joins me to share the story behind PuppyGraph’s “zero ETL” approach, which lets organizations query their existing data as a graph without ever moving or duplicating it. We discuss why graph databases, despite their promise, have struggled with mainstream adoption, often because of complex pipelines and heavy infrastructure requirements. Weimo explains how PuppyGraph borrows from his time at TigerGraph and Google’s F1 engine to build something new: a distributed query engine that maps tables into a logical graph and delivers subsecond performance on massive datasets. That shift opens the door for use cases in cybersecurity, fraud detection, and AI-driven applications where latency and accuracy matter most. We also unpack the developer experience. Instead of rewriting schemas or reloading data every time requirements change, PuppyGraph allows teams to define nodes and edges directly from existing tables. That design lowers the barrier for SQL-focused teams and accelerates time to value. Weimo even touches on the role of graph in reducing AI hallucinations, showing how structured relationships can make enterprise AI systems more reliable. What struck me most in our conversation is how PuppyGraph’s playful branding belies its serious engineering depth. Behind the “puppy” name lies a distributed engine built to scale with today’s data volumes, backed by strong early adoption and a team that listens closely to customer needs. Whether you’re exploring graph for cybersecurity, AI chatbots, or supply chain analytics, this discussion offers a glimpse of how the next generation of graph tech might finally break free from its niche and go mainstream. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37850040

3411: Why The Browser Is The New Security Perimeter 09/06/2025

3411: Why The Browser Is The New Security Perimeter When I invited Or Eshed, CEO and co-founder of LayerX Security, onto Tech Talks Daily, I wanted to challenge a blind spot most teams carry into work each day. We talk about phishing, ransomware, and endpoint controls, yet we skip the place where employees actually live online. The browser. That quiet tab bar has become the front door to identities, payments, SaaS, and now AI. Or calls it a different operating system in its own right, and once you hear his examples of how extensions can intercept cookies, mimic logins, or even meddle with AI chats, the penny drops fast. Here’s the thing. Blocking extensions across the board no longer fits how people work. Developers, marketers, sales teams, and support agents all lean on extensions for real productivity gains. Or’s argument is simple. If the business depends on extensions, security has to meet people where they are with continuous, risk-based controls inside the browser itself. That means assessing code, permissions, ownership changes, and live behaviors, not relying on a static allow list that grows and grows while attackers slip through the cracks. We also unpack Extensionpedia, LayerX’s free resource that lets anyone look up the risk profile of a specific extension. It is part education, part early warning system, and it serves a wider mission to raise the floor for everyone. Or shares how a technology alliance with Google has helped the team analyze extensions at serious scale, and why better data beats clever slogans in a space where signals change hour by hour. Malicious Extensions, AI Shortcuts, And The Culture Shift Security Needs One of the standout moments is a real-world story that starts at home and ends inside a corporate network. A spouse installs a screen-recording extension on a personal device, the browser profile syncs at work, and suddenly corporate credentials and sensitive sessions are mirrored to an untrusted machine. No shadowy APT needed. Just everyday sync doing exactly what it was designed to do. It is messy, human, and exactly why policy needs to be paired with continuous visibility in the browser. We explore the gray zone where productivity tools collide with privacy. Password managers, VPN helpers, and AI-everywhere extensions promise convenience, yet they can scrape data across SaaS apps or sync credentials in ways security leaders never intended. Or’s advice is refreshingly pragmatic. Assume extensions are staying. Instrument the browser, score risk in real time, and adapt access based on what an extension actually does, not what it claims on a store page. Looking ahead, Or sees the browser taking an even bigger role as email, SaaS, and AI agents converge in one place. With AI companies building their own browsers, the last mile of user interaction gets denser, faster, and more valuable to protect. If 99 percent of enterprise users already run at least one extension, the task is clear. Know which ones are in play, understand how they behave, and keep policy dynamic. If this conversation sparks a rethink of your own approach, check your extensions in Extensionpedia, and then consider what modern, in-browser controls would look like in your environment. After this episode, you may never look at that tidy row of icons the same way again. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37965150

3410: Smartly CEO Laura Desmond on how AI is Rewriting the Rules of AdTech 09/05/2025

3410: Smartly CEO Laura Desmond on how AI is Rewriting the Rules of AdTech I invited Laura Desmond, CEO of Smartly, to make sense of what feels like the biggest shake-up in marketing since the mobile era. She has led through every cycle I can remember, from the early internet to the rise of social, and she sees AI changing the rules faster than any previous wave. Across our conversation we unpack how AI is rewriting creative work, buying, and measurement, while forcing brands to rebuild trust with clear rules on data, models, and creator rights. Here’s the thing. Attention is shorter, and the thumb moves fast. Most people give an ad about two seconds, and video is taking over the feed. Laura expects video to account for three quarters of digital ads by 2026, which tracks with what I am seeing across every platform. Smartly is betting on that shift with tools that turn Shorts or TikToks into personalized CTV spots, and bring CTV signal back into social. The goal is simple to say and hard to pull off. Show every person something that feels made for them, then learn from the response and improve the next piece of creative in near real time. We also talk about why the ground is moving under search. A growing number of people, especially younger users, skip the front page of Google and ask an AI assistant instead. That changes how discovery works, how queries appear, and where ad products live. Laura thinks we are heading toward campaigns that cut across search, social, retail media, and CTV as one flowing video-first effort, with creative and media stitched together by software rather than teams tossing files over the wall. Results matter, and Laura shared two proof points I kept coming back to. Smartly’s platform has been validated by PwC for a 13 percent ROI lift across clients. The same study confirmed time savings that add up to 42 minutes a day for hands-on users. That reclaimed time funds the work that actually moves the needle, like faster A/B tests, sharper creative decisions, and better budget moves across channels. We also dig into conversational ads. In a recent test with Boots, Smartly’s format delivered roughly four times the return on investment versus business as usual, which speaks to how fast query-style interactions are shaping expectations. Trust sits in the middle of all this. Laura is clear that responsible AI is table stakes. Brands need controls to tune or override generated assets, clarity on data sources and model choice, and a stance on creator rights before any content goes live. Her view of AI is creative first. Automate the tedious parts. Keep people in charge of taste, tone, and brand. Use the feedback loop to learn faster, not to replace the team. We close on where this all leads. Expect brand experiences that blur physical and digital without losing the human spark. Stadiums full, stores buzzing, and at the same time richer virtual touchpoints, snackable video, and one-to-one conversations that feel helpful rather than creepy. If this is your world, Laura is hosting Smartly’s ADVANCE on September 17 in Brooklyn, and it looks set to be a real working session for marketers who want results, not theater. You can find details here: . Tune in if you want a candid, practical map for where creative, media, and AI are heading next, and how to measure what matters while keeping your brand worthy of trust. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/38093035

How Fugro is Using Tech to Chart the Ocean Floor 09/04/2025

3408: Lightricks, Open Source Video, and the Race for Faster Creativity 09/03/2025

3408: Lightricks, Open Source Video, and the Race for Faster Creativity Here’s the thing. Generative AI for visuals has shifted from a party trick to everyday craftwork, and few people sit closer to that shift than Ofir Bibi, VP of Research at Lightricks. In this conversation, I wanted to understand how a company famous for Facetune, Photoleap, and Videoleap is building for a future where creators expect speed, control, and choice without a headache. What I found was a story about building core technology that serves real creative workflows, not the other way around. Ofir traces Lightricks’ journey from clever on-device tricks that made small screens feel powerful to today’s foundation models running in the cloud. The constant thread is usability. Making complex editing feel simple requires smart decisions in the background, and that mindset has shaped everything from their early mobile apps to LTX Studio, the company’s multi-model creative platform. Across the last three years, generative features moved from novelty to necessity, and that reality forced a bigger question: when do you stop stitching together other people’s models and start crafting your own? That question led to LTXV, an open-source video generation model designed for speed, efficiency, and control. Ofir explains why Lightricks built it from scratch and why they shared the weights and trainer with the community. The result is a fast feedback loop where researchers, developers, and even competitors try ideas on a model that runs on consumer-grade hardware and can generate clips faster than they can be watched. The new LTXV 2B Distilled build continues that push toward quicker iteration and creator-friendly control, including arbitrary frame conditioning that suits animation and keyframe-driven workflows. We also talk about the changing data diet for training. Quantity is out. Quality and preparation matter. Licensed, high-aesthetic datasets and tighter curation produce models that understand prompts, motion, and physics with fewer weird edges. That discipline shows up in the product too. LTX Studio blends Lightricks tech with options from partners like Google’s Veo and Black Forest Labs’ Flux, then steers users toward the right model for the job through thoughtful UI. If you want the sharpest single shot, you can choose it. If you want fast, iterative tweaks for storytelling, LTXV is front and center. Looking ahead, Ofir sees a near future where models become broader and more multimodal, while creators and enterprises ask for local and on-prem options that keep data closer to home. That makes efficiency a feature, not a footnote. If you care about the craft of making, not just the spectacle, this episode offers a grounded view of how AI can actually serve creators. It left me convinced that speed and control are the real differentiators, and that open source can be a very practical way to get both. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37903905

How Altair’s AI Fabric Helps Businesses Move Beyond Pilot Projects 09/02/2025

How Altair’s AI Fabric Helps Businesses Move Beyond Pilot Projects Artificial intelligence is no longer confined to experiments in labs or one-off pilot projects. For many enterprises, it is becoming the backbone of how they operate, innovate, and compete. But as companies race to deploy AI, the biggest challenge is not whether the technology works, but whether the foundations exist to scale it safely and effectively. In this episode of Tech Talks Daily, I’m joined by Christian Buckner, Senior Vice President of Data and AI Platform at Altair, a company known for combining rocket science with data science. Christian unpacks the concept of an AI Fabric, a framework that harmonizes enterprise data and embeds AI directly into a universal model. Rather than scattered tools and isolated projects, the AI Fabric acts as a living system of intelligence, helping organizations move faster, make better decisions, and unlock new kinds of automation. We talk about how global enterprises from automotive suppliers to petrochemical giants are already using Altair’s technology to improve safety, optimize production, and cut costs. Christian shares examples including a transportation company that boosted revenue by $50 million in its first year of AI-driven dynamic pricing and a healthcare provider that saved $17 million in analysis time using knowledge graphs for drug discovery. The conversation also explores the hype and the risks around AI agents. While it is easy to spin up a proof of concept with a Python library, Christian explains why real enterprise impact requires governance, monitoring, and infrastructure to make agents trustworthy and sustainable. He likens it to building HR systems for AI, where agents need onboarding, oversight, and performance evaluation to operate alongside humans. We also touch on Altair’s acquisition by Siemens and what this means for the future of industrial AI. By integrating Altair’s data and AI expertise with Siemens’ deep industrial systems, enterprises can add intelligence without ripping out existing infrastructure. The result is not about replacing workers but enabling them to become what Christian calls “10x employees,” augmented by AI tools and agents that multiply their effectiveness. For anyone curious about how AI will change product design, operations, and enterprise decision-making, this episode offers a rare inside look at the technology foundations being built today. You can learn more at altair.com/ai-fabric. ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37761865

Arthur AI and the Future of Digital Co-Workers 09/01/2025

Arthur AI and the Future of Digital Co-Workers What if meetings stopped draining your time and instead became engines for action? That’s the question driving Christoph Fleischmann, CEO of Arthur AI, and the conversation in today’s episode of Tech Talks Daily. Christoph has spent his career at the intersection of human potential and technology, and now he’s leading a company that wants to change how enterprises actually get work done. Arthur AI isn’t another tool to add to the stack. It’s a digital co-worker—an intelligent presence that joins meetings, captures knowledge, and keeps teams aligned across time zones and formats. Whether in XR spaces, on the web, or through conversational interfaces, Arthur AI blends real-time and asynchronous collaboration. The aim is to replace endless, inefficient meetings with something more dynamic: an environment where humans and AI collaborate side by side to deliver outcomes. This conversation goes beyond theory. Christoph shares how Fortune 500 companies are already using Arthur AI to align global strategies, manage complex transformations, and modernize learning and development programs. He explains how their platform is built on enterprise-grade security and a flexible, LLM-agnostic architecture—critical foundations for companies wary of vendor lock-in or compliance risks. We also touch on the cultural shift of inviting AI to take a real seat at the table. From interviewing and project management to knowledge sharing, Arthur AI represents a new category of work experience, one where digital co-workers support people rather than replace them. For leaders tired of meetings that go nowhere and knowledge trapped in silos, this episode offers a glimpse of what smarter, faster collaboration looks like at scale. Could the blueprint for the future of digital work already be here? ********* Visit the Sponsor of Tech Talks Network: Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist /episode/index/show/techblogwriter/id/37780460

From Pinterest and Airbnb to Kumo AI: Reinventing Enterprise AI 08/31/2025

From Pinterest and Airbnb to Kumo AI: Reinventing Enterprise AI Here’s the thing. Most enterprise AI talk today starts with chatbots and ends with glossy demos. Meanwhile, the data that actually runs a business lives in rows, columns, and time stamps. That gap is where my conversation with Vanja Josifovski, CEO of Kumo AI really comes alive. Vanja has spent two and a half decades helping companies turn data into decisions, from research roles at Yahoo and Google to steering product and engineering at Pinterest through its IPO and later leading Airbnb Homes. He’s now building Kumo AI to answer an old question with a new approach: how do you get accurate, production-grade predictions from relational data without spending months crafting a bespoke model for each use case? Vanja explains why structured business data has been underserved for years. Images and text behave nicely compared to the messy reality of multiple tables, mixed data types, and event histories. Traditional teams anticipate a prediction need, then kick off a long feature engineering and modeling process. Kumo's Relational Foundation Model, or RFM, flips that script. Pre-trained on a large mix of public and synthetic data warehouses, it delivers task-agnostic, zero-shot predictions for problems like churn and fraud. That means you can ask the model questions directly of your data and get useful answers fast, then fine-tune for another 15 to 20 percent uplift when you’re ready to squeeze more from your full dataset. What stood out for me is how Kumo removes the grind of manual feature creation. Vanja draws a clear parallel to computer vision’s shift years ago, when teams stopped handcrafting edge detectors and started learning from raw pixels. By learning directly from raw tables, Kumo taps the entirety of the data rather than a bundle of human-crafted summaries. The payoff shows up in the numbers customers care about, with double-digit improvements against mature, well-defended baselines and the kind of time savings that change roadmaps. One customer built sixty models in two weeks, a job that would typically span a year or more. We also explore how this fits with the LLM moment. Vanja doesn’t position RFM as a replacement for language models. He frames it as a complement that fills an accuracy gap on tabular data where LLMs often drift. Think of RFM as part of an agentic toolbox: when an agent needs a reliable prediction from enterprise data, it can call Kumo instead of generating code, training a fresh model, or bluffing an answer. That design extends to the realities of production as well. Kumo’s fine-tuning and serving stack is built for high-QPS environments, the kind you see in recommendations and ad tech, where cost and latency matter. The training story is another thread you’ll hear in this episode. The team began with public datasets, then leaned into synthetic data to cover scenarios that are hard to source in the wild. Synthetic generation gives them better control over distribution shifts and edge cases, which speeds iteration and makes the foundation model more broadly capable upon arrival. If you care about measurable outcomes, this episode shows why CFOs pay attention when RFM lands. Vanja shares examples where a 20 to 30 percent lift translates into hundreds of thousands of additional monthly active users and direct revenue impact. That kind of improvement isn’t theory. It’s the difference between a model that nudges a metric and a model that moves it. By the end, you’ll have a clear picture of what Kumo AI is building, why relational data warrants its own foundation model, and how enterprises can move from wishful thinking to practical wins. Curious to try it yourself? Vanja also points to a sandbox where teams can load data and ask predictive questions within a notebook, then compare results against in-house models. If your AI plans keep stalling on tabular reality, this conversation offers a way forward that’s fast, accurate, and designed for the systems you already run. /episode/index/show/techblogwriter/id/37758460

VMware Explore 2025: Broadcom Showcases the Next Chapter of VCF Innovation 08/30/2025

VMware Explore 2025: Broadcom Showcases the Next Chapter of VCF Innovation When VMware Cloud Foundation 9.0 launched in June, it marked more than just another release. It was the clearest signal yet that Broadcom is betting big on the modern private cloud. In this episode of Tech Talks Daily, I sat down with Prashanth Shenoy, who leads marketing and learning for the VCF division at Broadcom, to discuss what the launch means for enterprises and how those themes are playing out live at VMware Explore in Las Vegas. Prashanth shares how VCF 9.0 was designed to help enterprises operate private clouds with the same simplicity and scale as public hyperscalers, while keeping sovereignty, security, and cost predictability front and center. He explains why this release is more than an infrastructure update. It’s a shift toward a workload-agnostic, developer-centric platform where virtual machines, containers, and AI workloads can run side by side with a consistent operational experience. We also unpack Broadcom’s headline announcements at the show. From making VCF an AI-native platform to embedding private AI services directly into the foundation, the message is clear: the AI pilots of the past are moving into production, and Broadcom wants VCF to be the default home for enterprise AI. Another major theme is cyber compliance at scale, with VCF now offering continuous enforcement, rapid ransomware recovery, and advanced security services that address today’s board-level concerns. But perhaps the biggest takeaway is the momentum. Nine of the top ten Fortune companies are now running on VCF, more than 100 million cores have been licensed, and dozens of enterprises—from global giants to mid-sized insurers—are on stage at VMware Explore sharing their adoption stories. The so-called “cloud reset” that Prashanth has written about is not just theory. Companies are rethinking their cloud strategies, seeking cost transparency, avoiding waste, and building resilient, AI-ready private clouds. This conversation highlights how Broadcom is doubling down on VCF with a singular focus, a massive R&D commitment, and a clear vision of where private cloud is headed. If you want to understand why private AI, developer services, and cyber resilience are now central to enterprise strategy, this is a conversation worth hearing. /episode/index/show/techblogwriter/id/38029325

Private AI Takes Center Stage at VMware Explore with Broadcom’s Tasha Drew 08/30/2025

Private AI Takes Center Stage at VMware Explore with Broadcom’s Tasha Drew At VMware Explore in Las Vegas, the buzz wasn’t just about generative AI, but about where and how it should run. My guest is Tasha Drew, Director of Engineering for the AI team in the VMware Cloud Foundation division at Broadcom, who has been at the center of this conversation. Fresh off the main stage, where she helped debut VMware’s new Private AI Services and Intelligent Assist for VMware Cloud Foundation, Tasha joins me to unpack what these announcements mean for enterprises grappling with privacy, cost, and integration challenges. Tasha explains why private AI is resonating so strongly in 2025, outlining the three pillars that define it: protecting sensitive intellectual property, managing regulated or high-value data, and ensuring role-based control of fine-tuned models. She shares how organizations often start their AI journey in the public cloud, but as experimentation turns to production, cost pressures, data compliance, and proximity to data drive them toward private AI. We also dive into VMware’s own evolution toward building an AI-native private cloud platform. Tasha highlights the journey from deep learning VMs and Jupyter notebooks to full AI platform services that empower IT teams to deliver models efficiently, save money, and accelerate deployment of retrieval-augmented generation (RAG) applications. She introduces Intelligent Assist for VMware Cloud Foundation, an AI-powered guide that helps teams navigate complex deployments with context-aware support and step-by-step instructions. Beyond the technology, Tasha reflects on the broader ecosystem shifts, from partnerships with NVIDIA and AMD to the role of Model Context Protocol (MCP) in breaking down integration barriers between enterprise systems. She believes MCP represents a turning point, enabling seamless workflows between platforms that historically lacked incentive to work together. This conversation captures a pivotal moment where private AI is moving from theory into enterprise adoption. For leaders weighing their next move, Tasha provides both the strategic framing and the technical insight to understand why private AI has become one of the most talked-about forces shaping enterprise IT today. /episode/index/show/techblogwriter/id/38025980

Inside Audi’s Smart Factory Vision at VMware Explore 08/29/2025

Fear vs FOMO: Kantar’s View on AI Adoption in Marketing 08/28/2025

AlgoSec on AI, Automation, and the Next Era of Network Management 08/27/2025

Claroty on Combating Model Poisoning and Adversarial Prompts 08/26/2025

Claroty on Combating Model Poisoning and Adversarial Prompts AI is rapidly becoming part of the healthcare system, powering everything from diagnostic tools and medical devices to patient monitoring and hospital operations. But while the potential is extraordinary, the risks are equally stark. Many hospitals are adopting AI without the safeguards needed to protect patient safety, leaving critical systems exposed to threats that most in the sector have never faced before. In this episode of Tech Talks Daily, I speak with Ty Greenhalgh, Healthcare Industry Principal at Claroty, about why healthcare’s AI rush could come at a dangerous cost if security does not keep pace. Ty explains how novel threats like adversarial prompts, model poisoning, and decision manipulation could compromise clinical systems in ways that are very different from traditional cyberattacks. These are not just theoretical scenarios. AI-driven misinformation or manipulated diagnostics could directly impact patient care. We explore why the first step for hospitals is building a clear AI asset inventory. Too many organizations are rolling out AI models without knowing where they are deployed, how they interact with other systems, or what risks they introduce. Ty draws parallels with the hasty adoption of electronic health records, which created unforeseen security gaps that still haunt the industry today. With regulatory frameworks like the UK’s AI Act and the EU’s AI regulation approaching, Ty stresses that hospitals cannot afford to wait for legislation. Immediate action is needed to implement risk frameworks, strengthen vendor accountability, and integrate real-time monitoring of AI alongside legacy devices. Only then can healthcare organizations gain the trust and resilience needed to safely embrace the benefits of AI. This is a timely conversation for leaders across healthcare and cybersecurity. The sector is on the edge of an AI revolution, but the choices made now will determine whether that revolution strengthens patient care or undermines it. You can learn more about Claroty’s approach to securing healthcare technology at claroty.com. /episode/index/show/techblogwriter/id/37835420

From Deliverables to Outcomes: Emergn’s New Playbook for Digital Success 08/25/2025

From Deliverables to Outcomes: Emergn’s New Playbook for Digital Success In November, Alex Adamopoulos, CEO of Emergn, joined me on Tech Talks Daily to talk about transformation fatigue and why so many well-intentioned change programs leave people drained rather than inspired. This time, he’s back with a sharper question: if traditional transformation is broken, what actually works? His answer is refreshingly direct. Product thinking is strategic thinking, and it belongs everywhere in the enterprise, not just in product teams. In our conversation, Alex explains why HR, finance, and even legal teams now need product strategy skills as much as engineers or designers. He introduces Praxis, Emergn’s newly launched platform that rebrands their long-standing VFQ approach and now embeds product thinking across entire organizations. With its AI-powered coach Stella, Praxis is designed to support continuous learning while helping teams make better day-to-day decisions. We also discuss why outcomes, not deliverables, have become the accurate measure of digital success. Alex likens it to leaders constantly returning to their boards like entrepreneurs on Shark Tank, demonstrating incremental value before securing the next round of support. This shift in accountability changes how teams plan, learn, and invest. Another essential thread is the link between burnout and broken transformation models. Alex recently co-authored a paper with Harvard professor Amy Edmondson on “Breaking the Failure Cycle,” and he shares how adopting a product mindset can help organizations move past fatigue by focusing on outcomes, embracing uncertainty, and avoiding the endless reinvention trap. Whether you’re in a global enterprise grappling with AI adoption or a smaller company rethinking strategy, this episode is a reminder that transformation is not a program but a continuous practice. Product thinking offers a practical path forward, one that makes strategy executable, measurable, and, most importantly, sustainable. /episode/index/show/techblogwriter/id/37816225

3397: From Wallets to Agents: The Next Chapter for Magic Labs 08/24/2025

3396: How Boson Protocol Is Creating the Infrastructure for AI-Driven Trade 08/24/2025

3396: How Boson Protocol Is Creating the Infrastructure for AI-Driven Trade In this episode of Tech Talks Daily, I’m joined for the third time by Justin Banon, the founder of Boson Protocol. A lot has changed since his last appearance. What started as a bold idea to decentralize e-commerce has now evolved into an ambitious, AI-first infrastructure aiming to redefine how we buy, sell, and interact with value itself. Justin walks us through the evolution of Boson. It began as a system for peer-to-peer digital and physical commerce, aiming to remove intermediaries like Amazon from the process. The next step was Fermion, a protocol designed specifically for high-value assets such as luxury goods, fine art, and real estate. Now, Boson is launching the Metasystem, a full-scale framework designed for what Justin calls “agentic commerce,” where AI agents transact on behalf of users. We talk about what that future looks like. Imagine an AI that not only shops for you but negotiates, verifies, and settles transactions securely. Justin predicts that in just a few years, these agents will outnumber human buyers and sellers by orders of magnitude. Boson’s mission is to build the decentralized rails for that world while avoiding the centralization traps of today’s tech giants. One particularly fascinating moment is our discussion of the Dolce & Gabbana glass suit. Purchased during the last bull run, this million-dollar piece of digital-physical fashion was not just fractionalized through Fermion but transformed into an AI persona called Dolce Lorien. This character now leads a gamified community campaign, rewarding participants with fractional ownership. It’s luxury meets sci-fi, wrapped in Web3 narrative. We also dig into what decentralized infrastructure really means for legacy brands. With Fermion, companies can reclaim the secondary market, verify resales, reconnect with past buyers, and turn their customer base into a true community. This isn’t just resale with a twist. It’s a new type of programmable loyalty system. Justin shares how AI doesn’t just enable commerce. It also supports his own personal growth. He reveals how he uses tools like ChatGPT and Speechify to create custom audio courses for niche subjects, walking through the woods while absorbing AI-generated masterclass-level insights. For those tired of seeing tech platforms control value creation while users are left with little ownership, this episode offers a glimpse of a different future. One where AI works directly for you. One where commerce is flexible, open, and fair. One where the infrastructure is built to stay that way. /episode/index/show/techblogwriter/id/37747540

3395: Communication Skills Every Tech Leader Needs 08/23/2025

3394: How Pet Media Group Is Using Tech to Protect Animals and Buyers 08/22/2025

3394: How Pet Media Group Is Using Tech to Protect Animals and Buyers The global pet industry has long been riddled with problems. From low-welfare breeding practices to online scams, the darker side of pet rehoming often goes unchecked. But what if there was a way to combine animal protection with a sustainable, profitable business model? In this episode of Tech Talks Daily, I speak with Axel Lagercrantz, co-founder and CEO of Pet Media Group, the company behind platforms like Pets4Homes in the UK and Lancaster Puppies in the US. Axel shares the story of how two friends with backgrounds in finance and tech came together to rethink what ethical pet ownership and commerce should look like. Since 2018, PMG has been working to remove anonymity and reduce fraud across pet marketplaces by embedding ethical standards directly into their platform’s infrastructure. We explore how PMG uses custom-built AI to scan tens of thousands of images every day for signs of mistreatment, as well as to flag suspicious documentation and chat messages. Axel explains why ID verification, device fingerprinting, and real-time fraud detection are essential to maintaining user trust, especially in a high-emotion, high-value market like pets. He also talks through the company’s expansion model, which focuses on acquiring local leaders and embedding PMG’s standards from the ground up. With operations now spanning six countries and a 50 percent EBITDA margin, PMG’s approach proves that protecting animals and scaling a business are not mutually exclusive goals. What stands out most is Axel’s clarity of purpose. PMG isn’t trying to digitize pet sales for convenience alone. The mission is to create a global infrastructure that prioritizes the welfare of animals and builds lasting trust between buyers and responsible breeders. If you care about technology that delivers real-world impact, this conversation will change how you think about one of the most overlooked parts of the digital economy. /episode/index/show/techblogwriter/id/37750805

3393: The Raiinmaker Model: Making Technology Work for the Many, Not the Few 08/21/2025

3392: Rebuilding the Internet: The Web3 Foundation’s Long Game 08/20/2025

3392: Rebuilding the Internet: The Web3 Foundation’s Long Game David Hawig never set out to work in blockchain. He began his career in health tech, drawn to the potential of scaling impactful solutions. But it was the promise of a more transparent and user-controlled internet that ultimately led him to the Web3 Foundation, where he now serves as Director of Ecosystem Development and Investor Relations. In our conversation on the Tech Talks Daily Podcast, David shares why Web3 is not just a trend or buzzword, but a complete rethink of how digital systems should function. He describes a world where users own their data, can verify transactions without relying on central authorities, and can move between services without friction. To David, the Web3 movement is not about hype or speculation. It's about enabling a future where the internet is built on truth, not trust. At the heart of the Web3 Foundation’s work is Polkadot, a protocol designed to solve the scalability and interoperability challenges that plague many early blockchain networks. David explains that Polkadot’s sharded infrastructure allows workloads to be split across participants in a trustless way. This setup not only enables more transactions but positions the ecosystem to support millions of users as mainstream adoption accelerates. That acceleration, he argues, is already happening. Thanks to new regulations like the Clarity Act and Genius Act in the US, enterprise adoption is becoming a reality. Where Web3 once attracted only startups and crypto-native communities, today major companies, including sports brands and entertainment groups, are actively building in the space. Unlike earlier efforts that felt more like PR stunts, these companies now see tangible benefits. Web3 can deliver faster, cheaper, and more flexible digital services, available 24/7, with no lock-in to single vendors. David is especially passionate about removing the barriers that have made Web3 feel intimidating to the average user. While early blockchain projects often demanded technical knowledge and wallet key management, he sees a future where users interact with Web3 products as easily as they would a mobile app. Behind the scenes, cryptography and decentralization are doing the heavy lifting, but from the user’s perspective, the experience is seamless. One area David is particularly excited about is decentralized storage. As more businesses realize the risks of relying on centralized cloud giants, alternatives are emerging that offer both cost advantages and greater control. He sees this as a critical part of the broader shift toward self-sovereign infrastructure. When asked if large corporations truly understand the scale of the disruption ahead, David is cautious but optimistic. Many established players, he says, still underestimate how quickly network effects can take hold. Once enough users and companies move into Web3 ecosystems, the old models will no longer be competitive. Whether it's financial services, social media, or identity management, the shift toward user-owned infrastructure will be difficult to reverse. Looking ahead to 2026 and beyond, David points to the upcoming Jam upgrade as a major milestone. This next evolution of the Polkadot network is designed to dramatically improve scalability, supporting not just crypto-native transactions but also broader use cases in gaming, ticketing, payments, and more. The goal is clear: create a robust, low-cost, interoperable infrastructure capable of supporting millions of users across different networks and applications. Before signing off, David leaves listeners with a recommendation. He suggests reading Man’s Search for Meaning by Viktor Frankl, a book he returns to often when reflecting on motivation and purpose. It’s a fitting choice for someone working at the edge of one of the most transformative shifts in modern tech. The Web3 Foundation is not just funding protocols or building tools. It's laying the groundwork for a future where the internet belongs to everyone. And if David’s predictions are right, that future may arrive faster than we think. /episode/index/show/techblogwriter/id/37747520

3391: What Wikidata Reveals About the Good Side of the Internet 08/19/2025

3391: What Wikidata Reveals About the Good Side of the Internet When most people think of Wikipedia, they picture an endless scroll of human-readable pages. But there’s another side to this ecosystem, one designed not just for people but also for machines. It’s called Wikidata, and if you haven’t heard of it, that’s exactly why this conversation matters. In this episode of Tech Talks Daily, I’m joined by Lydia Pintscher, Wikidata Portfolio Manager at Wikimedia Deutschland, for a deep look into how structured, open data is quietly powering civic tech, cultural preservation, and knowledge equity across the globe. Wikidata is the backbone that helps turn static knowledge into something living, adaptable, and scalable. With over 117 million items, 1.65 billion semantic statements, and more than 2.34 billion edits, it's become one of the largest collaborative datasets in the world. But it’s not just the size that makes it impressive. It’s what people are doing with it. Lydia shares how volunteers and developers are building tools for everything from investigative journalism to public libraries, all without needing deep pockets or proprietary infrastructure. This isn’t big tech. It’s a global, grassroots movement making open data work for the public good. We explore how tools like Toolforge and the Wikidata Query Service lower the barrier to entry, allowing civil society groups to build sophisticated applications that would otherwise be out of reach. Whether it’s helping connect citizens to government services or preserving disappearing languages, the use cases are multiplying fast. Lydia also reflects on how Wikidata fosters a sense of purpose for contributors, offering a rare example of what many call the good internet, where collaboration outweighs competition and building something meaningful beats chasing virality. If you’re curious about where open knowledge is headed, how structured data can be a force for social impact, or why Wikidata might be the most important project you’ve never fully explored, this episode offers a window into a future where machines help humans build something better, together. /episode/index/show/techblogwriter/id/37747355

3390: How Veritone Is Making AI Work for Media, Government, and Beyond 08/18/2025

3390: How Veritone Is Making AI Work for Media, Government, and Beyond What does it take to make AI actually work at enterprise scale? In this episode of Tech Talks Daily, I’m joined by Ryan Steelberg, CEO of Veritone, to unpack the very real challenges and opportunities that come with bringing artificial intelligence into complex industries like media, law enforcement, and government. Ryan has been building AI solutions long before it became headline news. He co-founded Veritone in 2014 with a mission to solve the unstructured data problem. Think audio, video, and other media that doesn't fit neatly into rows and columns. Now, Veritone isn’t just talking about AI. It’s powering more than 3,000 clients across sectors with real applications that drive measurable ROI. We get into what it means to work with unstructured data at scale, and how Veritone processed over 58 million hours of media in 2024 alone. Ryan explains why traditional enterprises struggle to operationalize AI and how Veritone has evolved from a platform company into a creator of end-user applications designed for impact. This includes ad optimization for ESPN and video redaction for law enforcement. What’s especially compelling is Veritone’s growing footprint in high-barrier sectors like federal defense and law enforcement. Ryan talks through what it took to become a prime contractor for the U.S. Air Force and Defense Logistics Agency, how Veritone adapted its stack for secure deployments, and why the key to adoption in these sectors isn’t just tech. It’s trust and proximity to mission-critical outcomes. We also discuss the company’s push into the $17 billion global training data market through the Veritone Data Repository. Ryan shares why VDR is gaining traction fast and how it positions the company as a key partner for the next generation of AI models. This isn’t a story of hype or futuristic promises. It’s a grounded look at what it really takes to scale AI in some of the most demanding enterprise environments. Whether you’re deep in the AI world or still figuring out where your business fits, Ryan’s perspective is honest, strategic, and full of lessons you can apply right now. /episode/index/show/techblogwriter/id/37845955

3389: Plaza Finance and the Rise of Programmable Derivatives 08/18/2025

3389: Plaza Finance and the Rise of Programmable Derivatives Is the future of finance programmable? In this episode of Tech Talks Daily, I’m joined by Ryan Galvankar, founder of Plaza Finance, to explore how programmable derivatives and on-chain bonds are reshaping the way we think about risk, leverage, and asset management in crypto. Plaza Finance isn’t just another DeFi protocol. Since launching its core system on Base in April 2025, the team has introduced two standout tokens: bondETH and levETH. These programmable derivative tokens split Ethereum into customizable risk profiles, allowing both institutional and retail investors to choose their exposure with precision. Under Ryan’s leadership, Plaza has already attracted over 600,000 testnet users, $2 million in early deposits, and $2.5 million in pre-seed funding. Ryan explains why this matters. Today’s DeFi tools tend to sit at either extreme—ultra-safe or wildly speculative. Plaza aims to bridge that gap with products that reflect the diversity of traditional finance, yet remain liquid and composable across Ethereum's ecosystem. He also shares why Ethereum staking plays a central role, and how integrations with lending platforms and cross-chain bridges will make these tokens even more powerful. But Ryan doesn’t stop at structured investing. He also launched OptFun, an ultra-short-term options trading platform that hit nearly $1 billion in trading volume within a month. It appeals to crypto natives seeking high-volatility speculation in a fair, on-chain environment. Together, these two platforms reflect what Ryan sees as a split in the future of DeFi: one track of thoughtful, long-term financial products that institutions will trust, and another track of high-speed, high-risk experimentation for users who live for volatility. He also gives his take on the rise of tokenized real-world assets, AI-generated portfolios, and what it will take to truly decentralize the next generation of finance. Whether you’re deep into DeFi or still watching from the sidelines, this conversation sheds light on a pivotal moment where programmable finance is becoming real, and access to tailored financial tools is expanding faster than ever. /episode/index/show/techblogwriter/id/37707295

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