Eye On A.I.
Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.
info_outline
#268 Kiren Sekar: The Future of Physical Operations Is AI-Powered (Here's Why)
07/06/2025
#268 Kiren Sekar: The Future of Physical Operations Is AI-Powered (Here's Why)
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. How AI Is Transforming the Physical World | Samsara’s Vision for the Future of Operations In this episode of Eye on AI, Craig Smith sits down with Kiren Sekar, Chief Product Officer at Samsara, to explore how AI, edge computing, and IoT are revolutionizing the world of physical operations - from fleets and factories to farms and field teams. Samsara has quietly become the digital backbone for thousands of frontline businesses, collecting trillions of data points across vehicles, tools, and teams. Kiren explains how they’re building AI-powered systems that don’t just collect data, they deliver real-time safety alerts, optimize routes, track fuel efficiency, and even coach drivers automatically. Whether you work in tech, operations, or AI, this episode shows how AI is finally meeting the real world. Check our Samsara, AI Build for Physical Operations: Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Preview (02:01) Kiren Sekar’s Background and Why Samsara Was Founded (06:38) The Real-World Impact of Samsara’s AI Systems (09:04) What Changed After Samsara Went Public (11:09) How Samsara Gives Businesses Visibility Into Operations (13:08) The Hardware and Cellular Network Powering Samsara (14:13) AI to Detect Driving Risks (23:13) Tracking Every Asset: From Cranes to Toolkits (25:20) Why Even Mid-Sized Companies Can Use Samsara Easily (27:25) Regional Dashboards and AI Insights for Executives (29:57) How Samsara Decides Where to Apply AI (32:54) Can AI Read Handwritten Forms? (35:31) The AI Models Samsara Uses (39:21) What Samsara Processes at the Edge vs in the Cloud (43:00) Why Samsara Keeps Its R&D Team Small and Fast (46:35) Why Legacy Industries Are Finally Adopting AI (49:12) What Agentic AI Workflows Look Like at Samsara (54:53) What’s Next: AI Voice Assistants for Field Worker
/episode/index/show/aneyeonai/id/37292580
info_outline
#267 Nabil Bukhari: Exploring the Future of AI-Powered Enterprise Networking with Extreme Networks
07/02/2025
#267 Nabil Bukhari: Exploring the Future of AI-Powered Enterprise Networking with Extreme Networks
What does the future of enterprise networking really look like? In this episode, Extreme Networks’ Chief Product & Technology Officer Nabil Bukhari joins Craig to explore how AI, autonomous agents, and platform thinking are transforming the core infrastructure of modern businesses. From managing mission-critical networks to building agentic systems that collaborate, troubleshoot, and scale autonomously - this is a deep dive into how connectivity is being redefined from the ground up. Whether you’re a tech leader, CIO, product builder, or simply curious about how infrastructure evolves, this conversation reveals where the enterprise is headed next. Check out Extreme Networks: Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Preview (01:02) Introducing Nabil Bukhari & Extreme Networks (05:24) Why Global Connectivity Is Still Accelerating (07:54) How Enterprise Data Flows Across Modern Networks (12:34) Networking for AI vs. Built-in AI (14:12) Platform One & Agentic AI Systems Explained (21:20) Human-in-the-Loop, Over-the-Loop, and Above-the-Loop (23:35) Why AI Guardrails Must Be Baked into the Architecture (27:33) Introducing the ARC Framework (31:15) Persona-Based Interfaces for NetOps, CFOs & CMOs (33:25) The Problem with Chatbots (36:06) Enterprise vs. Public Networks (38:38) Global Connectivity Infrastructure & Use Case Variability (44:29) How Secure and Resilient Are Enterprise Networks? (52:24) In-House AI for Critical Infrastructure
/episode/index/show/aneyeonai/id/37256480
info_outline
#266 Andy Kurtzig: How Pearl Uses AI + Human Experts In Professional Services
06/29/2025
#266 Andy Kurtzig: How Pearl Uses AI + Human Experts In Professional Services
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What if AI could actually be trusted in healthcare, law, or even car repair? In this episode, Andy Kurtzig, founder and CEO of Pearl (formerly JustAnswer), reveals how his platform is solving the biggest problems in AI: hallucinations, liability, and monetization. Pearl blends large language models with real human experts across 700+ categories—so users get AI speed and human-verified accuracy. Whether you're a doctor, mechanic, or just someone with a question, Pearl offers fast, affordable, and expert-backed answers—without the risk of misinformation. If you’re building in AI, working in a regulated industry, or just curious about the future of trusted automation—this episode is for you. Check out Pearl, AI Enhanced Human Expertise: Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Introduction (03:20) Why Pearl Focuses on High-Stakes Industries (06:10) How Pearl Reduces AI Hallucinations with Human Trust Scores (10:11) Pearl.com’s Ideal Customers (14:14) Solving AI Liability with Platform Protection (23:27) The Three Big Problems in AI: Risk, Quality, and Monetization (29:00) Why Human-in-the-Loop Is the Future of AI (33:26) Pearl’s API: Bringing Verified Experts to Any App (39:27) Building Trust in AI Through Human Validation (41:03) The Road Ahead for Pearl and Human-Centered AI
/episode/index/show/aneyeonai/id/37206685
info_outline
#265 Jeff Lu: How Akool Uses Gen AI to Make Live AI Avatars & Voices
06/27/2025
#265 Jeff Lu: How Akool Uses Gen AI to Make Live AI Avatars & Voices
What if you could translate any video into any language—instantly—and make it look like the speaker was really speaking it? In this episode of Eye on AI, host Craig Smith sits down with Jeff Liu, founder and CEO of Akool, to explore how AI avatars and real-time video translation are eliminating global language barriers. With a background at Apple, Google, and Stanford, Jeff is leading Akool to the frontier of generative AI: cloning faces, voices, and emotions in live video streams. We dive into the technical architecture behind Akool’s real-time avatars, the role of large language models in translation latency, and what the future looks like when the need to "learn languages" may disappear. Whether you're a content creator, marketer, technologist, or just curious about what’s next in AI and communication, this episode is a must-listen. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Creating Digital Clones with AI (01:20) Jeff Liu’s Journey from Big Tech to Startup Founder (02:54) What Akool Does and Who It's For (07:11) Inside the Live AI Avatar Suite (10:32) How Akool Powers Real-Time AI Avatars (16:05) Solving Language Translation with Avatars (21:40) Translating YouTube Videos with One Click (28:36) The Technology Behind Real-Time Translation (33:22) Competing with Tech Giants Like Google (36:26) Akool's Vision (39:36) Avatar Types: Instant, Studio, and Ultra explained (43:39) Building Emotional Nuance into Voice and Video
/episode/index/show/aneyeonai/id/37178040
info_outline
#264 Amr Awadallah: Vectara’s Mission To Make AI Hallucination-Free & Enterprise Ready
06/22/2025
#264 Amr Awadallah: Vectara’s Mission To Make AI Hallucination-Free & Enterprise Ready
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What’s stopping large language models from being truly enterprise-ready? In this episode, Vectara CEO and co-founder Amr Awadallah breaks down how his team is solving one of AI’s biggest problems: hallucinations. From his early work at Yahoo and Cloudera to building Vectara, Amr shares his mission to make AI accurate, secure, and explainable. He dives deep into why RAG (Retrieval-Augmented Generation) is essential, how Vectara detects hallucinations in real-time, and why trust and transparency are non-negotiable for AI in business. Whether you're a developer, founder, or enterprise leader, this conversation sheds light on the future of safe, reliable, and production-ready AI. Don’t miss this if you want to understand how AI will really be used at scale. Stay Updated: Craig Smith on X: Eye on A.I. on X:
/episode/index/show/aneyeonai/id/37102845
info_outline
#263 Jarek Kutylowski: How DeepL Is Using AI to Break Language Barriers
06/18/2025
#263 Jarek Kutylowski: How DeepL Is Using AI to Break Language Barriers
What if language was no longer a barrier to global business? In this episode, DeepL CEO Jarek Kutylowski joins Craig Smith to unpack how AI-powered translation is reshaping the way companies communicate across borders. From real-time speech tools to enterprise-grade language workflows, Jarek shares DeepL’s journey, the tech behind their LLMs, and why accuracy, nuance, and localization matter more than ever. If you're building for a global audience, this conversation is a must-listen. About Jarek: Dr. Jaroslaw “Jarek” Kutylowski is the founder and CEO of DeepL, the Cologne-based Language AI company transforming global communication and breaking down language barriers for businesses worldwide. Born in Poland and having spent a large part of his life in Germany, Jarek brings an international perspective and a lifelong passion for technology - a developer at heart, he began coding at just 10 years old, building tools he found useful in daily life. He holds a PhD in Computer Science with a focus on mathematics and has held roles at several tech companies prior to founding DeepL. Under his leadership, DeepL has grown rapidly, expanding its Language AI platform to offer highly accurate and nuanced human-like translation in both written and spoken formats, as well as a contextual AI writing assistant. Today, over 200,000 businesses and governments - and millions of individuals across 228 global markets - trust DeepL for secure, seamless and effective communication. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Introduction to DeepL and Jarek’s Vision (05:09) DeepL’s Technology Evolution (08:17) The DeepL Platform: Products, APIs, and Enterprise Use Cases (12:39) Why DeepL Outperforms Consumer Tools (15:14) How Enterprises Use DeepL (17:05) DeepL’s Translation Accuracy (21:20) Breaking Language Barriers in Global Workforces (23:46) A Future Without Language Barriers (27:19) Expanding Language Coverage and Industry Verticals (31:44) DeepL’s Role in High-Compliance Sectors (34:04) Tackling Latency and Real-Time Use Cases (38:38) DeepL as the Translation Engine Behind Other Products (42:40) Partnering with News Media and Government (45:40) Pricing Models and Accessibility (46:24) The Human Impact of AI-Powered Language Tools (49:22) What’s Next for DeepL and Global Communication
/episode/index/show/aneyeonai/id/37060065
info_outline
#262 Deepak Chopra: How to Use AI to Expand Human Consciousness
06/15/2025
#262 Deepak Chopra: How to Use AI to Expand Human Consciousness
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. Can AI expand human consciousness? Or is it just a simulation of wisdom? In this mind-bending episode of Eye on AI, host Craig Smith sits down with world-renowned spiritual teacher and author Deepak Chopra to explore the future of Artificial Intelligence, consciousness, health, and spiritual awakening. Deepak unpacks the ideas behind his latest book, Digital Dharma, and shares how his team built a small language model—DeepakChopra.ai—designed to serve as a digital health and spiritual guide. Together, they dive deep into quantum theory, the illusion of the physical world, and why consciousness is not something AI can ever possess—but it can help us reach it. Whether you're an AI enthusiast, a spiritual seeker, or simply curious about the future of human evolution, this episode will challenge your assumptions and expand your perspective. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Why Deepak Chopra Is Entering the AI Space (04:05) The Promise and Peril of the AI Revolution (09:47) How Deepak Chopra Built His Own AI Model (13:58) Is AI the Future of Human Evolution? (15:39) How the AI Landscape Has Evolved Over Time (21:22) AI in Preventative Healthcare (24:49) Key Insights from “Digital Dharma” (25:40) Using Prompt Engineering for Inner Growth (38:28) Exploring Human Potential Through AI (43:16) Can AI Understand Human Emotions? (47:00) Spiritual Awakening in the Age of AI (50:54) The Future of AI and Consciousness
/episode/index/show/aneyeonai/id/37014285
info_outline
#261 Jonathan Frankle: How Databricks is Disrupting AI Model Training
06/12/2025
#261 Jonathan Frankle: How Databricks is Disrupting AI Model Training
This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. Try OCI for free at What if you could fine-tune an AI model without any labeled data—and still outperform traditional training methods? In this episode of Eye on AI, we sit down with Jonathan Frankle, Chief Scientist at Databricks and co-founder of MosaicML, to explore TAO (Test-time Adaptive Optimization)—Databricks’ breakthrough tuning method that’s transforming how enterprises build and scale large language models (LLMs). Jonathan explains how TAO uses reinforcement learning and synthetic data to train models without the need for expensive, time-consuming annotation. We dive into how TAO compares to supervised fine-tuning, why Databricks built their own reward model (DBRM), and how this system allows for continual improvement, lower inference costs, and faster enterprise AI deployment. Whether you're an AI researcher, enterprise leader, or someone curious about the future of model customization, this episode will change how you think about training and deploying AI. Explore the latest breakthroughs in data and AI from Databricks: Stay Updated: Craig Smith on X: Eye on A.I. on X:
/episode/index/show/aneyeonai/id/36969555
info_outline
#260 Ash Anwar: How Molecular You Uses AI for Early Disease Detection
06/09/2025
#260 Ash Anwar: How Molecular You Uses AI for Early Disease Detection
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What if your blood could reveal the future of your health - years before symptoms ever appear? In this episode of Eye on AI, Craig Smith sits down with Ash Anwar, co-founder of Molecular You, to explore how AI and advanced biomarker analysis are transforming how we detect and prevent disease. From a real-life case where stage 1 pancreatic cancer was caught early, to the science behind tracking 250+ dynamic biomarkers, Ash breaks down how Molecular You is shifting healthcare from reactive treatment to proactive longevity. They dive into the limitations of genetic testing, the power of machine learning models trained on clinical data, and how personalized action plans are helping individuals take control of their health in real time. If you're curious about the intersection of AI, diagnostics, and the future of preventive medicine—this is a conversation you won't want to miss. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) How AI Can Predict Disease Before It Happens (02:02) Meet Ash Anwar: From Scientist to Health Tech Leader (06:31) What Is Molecular You and How It Works (09:43) Why Biomarker Tracking Over Time Is a Game-Changer (15:46) How Molecular You Detected Stage 1 Pancreatic Cancer (23:15) Biomarkers vs Genetics: What Really Matters (28:11) The AI Models Behind Early Disease Detection (32:37) How the Product Works for Clinics and Consumers (35:05) Who They Compete With and What Makes Them Different (37:34) Research vs Product: The Cancer Risk Challenge (43:43) How Often Should You Get Tested?
/episode/index/show/aneyeonai/id/36918300
info_outline
#259 Anjney Midha: a16z’s Strategy to Turn AI Startups into Unicorns
06/02/2025
#259 Anjney Midha: a16z’s Strategy to Turn AI Startups into Unicorns
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What does it really take to turn cutting-edge AI research into a successful foundation model company? In this episode of Eye on AI, we sit down with Anjney Midha, General Partner at a16z, to unpack how he helps scientists and researchers transform their breakthroughs into scalable, real-world AI businesses. From his early backing of Anthropic to launching Mistral and Black Forest Labs, Anjney shares a behind-the-scenes look at how AI infrastructure companies are born. We dive into the critical challenges of model reliability, evaluation beyond academic benchmarks, and the rise of hybrid architectures combining transformers with diffusion and LSTMs. If you're building in AI or investing in it, this is the roadmap to what's next. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Turning AI Research into Real Companies (02:08) Anjney’s Journey into Venture Capital (05:44) The Birth of Anthropic (08:26) Backing Mistral and Stable Diffusion (13:16) Are Transformers Really Enough? (18:36) Why AI Evaluation Is Broken (22:10) Making AI Models More Interpretable (28:38) The Real Potential of AI Agents (32:43) How a16z Spots AI Breakthroughs (37:45) Investing Like It’s the 1970s (43:31) What AI Voice Tech Needs Right Now (46:32) Models vs Products (51:17) What’s Holding Back AI Agents (55:41) Anjney Startup Investing Strategy
/episode/index/show/aneyeonai/id/36814815
info_outline
#258 Brian Peterson: How Dialpad is Building the Future of AI-Powered Communication
05/29/2025
#258 Brian Peterson: How Dialpad is Building the Future of AI-Powered Communication
What happens when you combine 8 billion minutes of voice data with a full-stack AI engine? Yes, that’s what Dialpad is doing. In this episode, Brian Peterson, CTO and Co-Founder, breaks down how they’ve built an AI-powered communications platform from the ground up. From real-time sales coaching and AI-driven support agents to predictive analytics that can spot churn before it happens, Brian shares why owning the full stack — infrastructure, LLMs, and data is the only way to deliver truly intelligent customer experience. If you’re curious about the future of AI in business communication, this is the episode to watch. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Brian’s Founding Story (03:56) What Dialpad Actually Does Today (05:17) Is Voice the Most Valuable Untapped Data Source? (07:41) Inside DialpadGPT (10:10) AI Solutions for Sales, Support & Collaboration (12:24) Owning the Entire Customer Journey with Unified Comms (14:11) How Dialpad Stays Ahead in the AI Race (17:50) Real-Time AI Coaching & Playbooks (22:32) Why Most Enterprises are Behind in AI Adoption (25:28) Action-Oriented AI Agents (32:40) What’s Next for AI in Customer Communication
/episode/index/show/aneyeonai/id/36767295
info_outline
#257 Ankur Banerjee: How cheqd.io Is Building Trust for AI Agents with Decentralized Identity
05/25/2025
#257 Ankur Banerjee: How cheqd.io Is Building Trust for AI Agents with Decentralized Identity
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What if AI agents needed digital passports to act on your behalf? In this episode, Ankur Banerjee, Co-Founder and CTO of cheqd.io, reveals how decentralized identity is becoming the foundation of the AI agent economy. From booking Taylor Swift tickets with an agent to proving you're a real person online, we explore why identity and trust are the hidden infrastructure shaping the future of AI. Ankur explains how cheqd is building privacy-first tools that let AI agents verify who they are, what they can do, and who they're working for, all without handing over your data to big tech. We dig into the rise of digital credentials, the limits of biometrics, and how protocols like MCP are making the internet safe for autonomous agents. If you've ever wondered how AI will operate on your behalf in the real world, this conversation offers a glimpse into what's coming next. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Why AI Needs Identity (02:16) Ankur’s Path to cheqd (05:39) Delegating Tasks to AI Agents (11:26) Identity Lessons from Governments (17:25) Trusting AI with Digital Credentials (23:42) The Problem with Biometrics (30:49) Web Standards for Agent Identity (36:46) MCP and Agent Interoperability (48:47) Bridging Web2 and Web3 Identity (55:18) Why Companies Should Care About Decentralized ID
/episode/index/show/aneyeonai/id/36701460
info_outline
#256 Stephen Schmidt: Inside Amazon’s AI-Powered Cybersecurity Strategy
05/22/2025
#256 Stephen Schmidt: Inside Amazon’s AI-Powered Cybersecurity Strategy
Can Generative AI Be Secured? Amazon's Chief Security Officer Weighs In In this episode of Eye on AI, Amazon's Chief Security Officer Stephen Schmidt pulls back the curtain on how Amazon is using AI-powered cybersecurity to defend against real-world threats. From global honeypots to intelligent alarm systems and secure AI agent networks, Steve shares never-before-heard details on how Amazon is protecting both its infrastructure and your data in the age of generative AI. We dive deep into: Amazon's MadPot honeypot network and how it tracks adversaries in 90 seconds The role of AI in threat detection, alarm triage, and code validation Why open-source vs. closed-source models are a real security debate The critical need for data privacy, secure LLM usage, and agent oversight Amazon's $5M+ Nova Trusted AI Challenge to battle adversarial code generation Whether you're building AI tools, deploying models at scale, or just want to understand how the future of cybersecurity is evolving—this episode is a must-listen. Don’t forget to like, subscribe, and turn on notifications to stay updated on the latest in AI, security, and innovation. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Preview (00:52) Stephen Schmidt’s Role and Background at Amazon (02:11) Inside Amazon's Global Honeypot Network (MadPot) (05:26) How Amazon Shares Threat Intel Through GuardDuty (08:06) Are Cybercriminals Using AI? (10:28) Open Source vs Closed Source AI Security Debate (13:09) What Is Amazon GuardDuty (17:44) How Amazon Protects Customer Data at Scale (20:18) Can Autonomous AI Agents Handle Security? (25:14) How Amazon Empowers SMBs with Agent-Driven Security (26:18) What Tools Power Amazon’s Security Agents? (29:25) AI Security Basics (35:34) Securing AI-Generated Code (37:26) Are Models Learning from Our Queries? (39:44) Risks of Agent-to-Agent Data Sharing (42:08) Inside the $5M Nova Trusted AI Security Challenge (47:01) Supply Chain Attacks and State Actor Tactics (51:32) How Many True Adversaries Are Out There? (53:04) What Everyone Needs to Know About AI Security
/episode/index/show/aneyeonai/id/36667900
info_outline
#255 Eric Topol: Why AI is the Most Powerful Tool in Healthcare Now
05/18/2025
#255 Eric Topol: Why AI is the Most Powerful Tool in Healthcare Now
AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. What if AI could predict exactly when you'd get sick—and help you prevent it? In this episode of Eye on AI, Dr. Eric Topol, world-renowned cardiologist, author, and AI health pioneer, joins us to unveil the future of preventive medicine. We dive deep into the themes of his new book Super Agers, which lays out a groundbreaking blueprint for extending healthspan—not just lifespan—through the power of multimodal AI and deep biological data. Dr. Topol explains how AI models can now analyze a full-stack of human data—genomics, proteomics, metabolomics, microbiome, and more—to forecast age-related diseases like cancer, Alzheimer’s, and heart disease decades before symptoms appear. This isn’t science fiction. It’s here now. If you're interested in the intersection of AI, longevity, and the future of medicine, this is a must-listen. Where AI Works tackles the big questions shaping AI’s role in business today, cutting through the hype to deliver actionable insights for leaders. Brought to you by the Wharton School, in collaboration with Accenture, this podcast combines cutting-edge research with real-world case studies to uncover how top companies are using AI to upskill workforces, enhance customer experiences, boost productivity, and streamline operations. Check it out: Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) The Power of Precision Medical Forecasting (01:53) Eric Topol’s Journey into Digital & AI Medicine (03:27) Using AI to Prevent Aging-Related Diseases (05:25) The Challenge of Health Data Privacy & Ownership (09:05) Genetic Risk to Deep Data Insights (11:20) Personalized Prevention Through Lifestyle & Biomarkers (13:59) Why Anti-Aging Drugs Are Still Years Away (16:18) What are Organ Clocks (19:34) The Longevity Industry’s Flawed Use of AI (21:59) Top AI Pioneers Endorse “Super Agers” (24:21) Which Longevity Startups Are Getting It Right? (26:27) Why Topol Refuses to Join Longevity Startups (28:57) Topol’s Own Health Data & Lessons Learned (30:25) How Accurate Is AI at Predicting Disease Timing? (31:47) The Truth About Genetic Risk and Cancer Detection (33:33) AI-Driven Cancer Detection: A Smarter Approach (38:51) How Precision Medicine Has Evolved (41:02) The Risky Reality of Anti-Aging Interventions (44:39) Why Healthspan Matters More Than Lifespan
/episode/index/show/aneyeonai/id/36611435
info_outline
#254 Prashanth: Why Developers Still Trust Stack Overflow in the Age of AI
05/14/2025
#254 Prashanth: Why Developers Still Trust Stack Overflow in the Age of AI
This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. Offer only for new US customers with a minimum financial commitment. See if you qualify for half off at In this episode of Eye on AI, host Craig Smith speaks with Prashanth Chandrasekar, CEO of Stack Overflow, about how one of the internet’s most trusted platforms for developers is adapting to the era of generative AI. With over 60 million human-curated Q&A pairs, Stack Overflow is now at the center of AI development — not as a competitor to large language models like ChatGPT, but as a foundational knowledge base that powers them. Prashanth breaks down how Stack Overflow is partnering with OpenAI, Google, and other LLM providers to license its data and improve AI accuracy, while also protecting the integrity of its community. He explains the rise of OverflowAI, how Stack Overflow for Teams is fueling enterprise-grade co-pilots, and why developers still rely on expert human input when AI hits its “complexity cliff.” The conversation covers everything from hallucination problems and trust issues in AI-generated code to the monetization of developer data and the evolving interface of the web. If you want to understand the future of developer tools, AI coding assistants, and how human knowledge will coexist with autonomous agents, this episode is a must-listen. Subscribe for more deep dives into how AI is reshaping the world of software, enterprise, and innovation. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Intro (02:31) Prashanth’s Journey from Developer to CEO (05:18) Why Stack Overflow is Different from GitHub (08:51) The Power of Community and Human-Curated Knowledge (12:53) Stack Overflow’s Data Strategy for AI Training (17:26) Why Stack Overflow Isn’t Competing with OpenAI (20:36) How Stack Overflow Powers Enterprise AI Agents (26:13) OverflowAI, Gemini, and the Future of Dev Workflows (30:09) Inside Stack Overflow for Teams (33:29) Safeguarding Quality: The Fight Against AI Slop (38:32) Licensing, Attribution, and Protecting the Knowledge Base (43:19) Business Strategy in the Age of Generative AI
/episode/index/show/aneyeonai/id/36559785
info_outline
#253 Ivan Shkvarun: Inside the Fight Against AI-Driven Cybercrime
05/11/2025
#253 Ivan Shkvarun: Inside the Fight Against AI-Driven Cybercrime
This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking.Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience. Visit to learn more. In this episode of Eye on AI, we sit down with Ivan Shkvarun, CEO of Social Links and founder of the Dark Side AI Initiative, to uncover how cybercriminals are leveraging generative AI to orchestrate fraud, deepfakes, and large-scale digital attacks—often with just a few lines of code. Ivan shares how his team is building real-time OSINT (Open Source Intelligence) tools to help governments, enterprises, and law enforcement fight back. From dark web monitoring to ethical AI frameworks, we explore what it takes to protect the digital world from the next wave of AI-powered crime. Whether you're in tech, cybersecurity, or policy—this conversation is a wake-up call. AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit and add your support. From cybersecurity to law enforcement — discover how Social Links brings the full potential of OSINT to your team at Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Preview (02:11) Meet Ivan Shkvarun & Social Links (03:41) Launching the Dark Side AI Initiative (05:16) What OSINT Actually Means Today (08:39) How Law Enforcement Trace Digital Footprints (12:50) Connecting Surface Web to Darknet (16:12) OSINT Methodology in Action (20:23) Why Most Companies Waste Their Own Data (21:09) Cybersecurity Threats Beyond the IT Department (26:25) BrightSide AI vs. DarkSide AI (30:10) Should AI-Generated Content Be Labeled? (31:26) Why We Can’t “Stop” AI (35:37) Why AI-Driven Fraud Is Exploding (41:39) The Reality of Criminal Syndicates
/episode/index/show/aneyeonai/id/36521255
info_outline
#252 Jeffrey Hammond: How to Build Scalable GenAI Products (AWS Strategy)
05/09/2025
#252 Jeffrey Hammond: How to Build Scalable GenAI Products (AWS Strategy)
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more.NetSuite is offering a one-of-a-kind flexible financing program. Head to to know more. AWS partnered with Forrester Research to understand how software providers (ISVs), in particular, plan to drive profitable growth with generative AI, how they are uniquely approaching generative AI development, and the key challenges they’re facing. In this conversation with Jeffrey Hammond, Global ISV Product Strategist at AWS, he dives into the findings of the research and discusses how — particularly with AWS’s help — ISVs can drive profitable growth and succeed in the gen AI gold rush. Jeffrey helps software product management leaders leverage AWS cloud services to accelerate product delivery, create new revenue streams, reduce technical debt, and optimize operational costs. You’ll learn: Why “toil reduction” is the fastest path to GenAI ROI How AWS’s GenAI Innovation Center helps companies cut costs and ship faster What most ISVs get wrong about trust, security, and customer communication The secret to scalable AI product pricing—and what Canva got right Why agentic workflows and federated models are the next frontier in software Whether you're building on AWS or just exploring GenAI adoption, this conversation is packed with frameworks, examples, and strategy. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) The Future of Work with Generative AI (03:20) Inside AWS: How Jeffrey Supports AI Innovation (06:00) What the Forrester Survey Reveals About AI Adoption (09:15) From Hype to Value: Building Real GenAI Use Cases (13:45) How ISVs Are Reducing Toil and Driving Efficiency (17:10) Balancing Innovation with Trust and Security (22:00) AWS Programs That Help ISVs Win with AI (28:00) GenAI Product Strategy: Accuracy, Cost & Pricing Models (34:30) Overcoming Infrastructure Challenges in GenAI (39:45) The Rise of Agentic Workflows and Interoperability (46:00) The Biggest Tech Disruption in Decades?
/episode/index/show/aneyeonai/id/36506995
info_outline
#251 Sid Sheth: How d-Matrix is Disrupting AI Inference in 2025
04/30/2025
#251 Sid Sheth: How d-Matrix is Disrupting AI Inference in 2025
This episode is sponsored by the DFINITY Foundation. DFINITY Foundation's mission is to develop and contribute technology that enables the Internet Computer (ICP) blockchain and its ecosystem, aiming to shift cloud computing into a fully decentralized state. Find out more at In this episode of Eye on AI, we sit down with Sid Sheth, CEO and Co-Founder of d-Matrix, to explore how his company is revolutionizing AI inference hardware and taking on industry giants like NVIDIA. Sid shares his journey from building multi-billion-dollar businesses in semiconductors to founding d-Matrix—a startup focused on generative AI inference, chiplet-based architecture, and ultra-low latency AI acceleration. We break down: Why the future of AI lies in inference, not training How d-Matrix’s Corsair PCIe accelerator outperforms NVIDIA's H200 The role of in-memory compute and high bandwidth memory in next-gen AI chips How d-Matrix integrates seamlessly into hyperscaler and enterprise cloud environments Why AI infrastructure is becoming heterogeneous and what that means for developers The global outlook on inference chips—from the US to APAC and beyond How Sid plans to build the next NVIDIA-level company from the ground up. Whether you're building in AI infrastructure, investing in semiconductors, or just curious about the future of generative AI at scale, this episode is packed with value. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Intro (02:46) Introducing Sid Sheth (05:27) Why He Started d-Matrix (07:28) Lessons from Building a $2.5B Chip Business (11:52) How d-Matrix Prototypes New Chips (15:06) Working with Hyperscalers Like Google & Amazon (17:27) What’s Inside the Corsair AI Accelerator (21:12) How d-Matrix Beats NVIDIA on Chip Efficiency (24:10) The Memory Bandwidth Advantage Explained (26:27) Running Massive AI Models at High Speed (30:20) Why Inference Isn’t One-Size-Fits-All (32:40) The Future of AI Hardware (36:28) Supporting Llama 3 and Other Open Models (40:16) Is the Inference Market Big Enough? (43:21) Why the US Is Still the Key Market (46:39) Can India Compete in the AI Chip Race? (49:09) Will China Catch Up on AI Hardware?
/episode/index/show/aneyeonai/id/36370900
info_outline
#250 Pedro Domingos on the Real Path to AGI
04/24/2025
#250 Pedro Domingos on the Real Path to AGI
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to Can AI Ever Reach AGI? Pedro Domingos Explains the Missing Link In this episode of Eye on AI, renowned computer scientist and author of The Master Algorithm, Pedro Domingos, breaks down what’s still missing in our race toward Artificial General Intelligence (AGI) — and why the path forward requires a radical unification of AI's five foundational paradigms: Symbolists, Connectionists, Bayesians, Evolutionaries, and Analogizers. Topics covered: Why deep learning alone won’t achieve AGI How reasoning by analogy could unlock true machine creativity The role of evolutionary algorithms in building intelligent systems Why transformers like GPT-4 are impressive—but incomplete The danger of hype from tech leaders vs. the real science behind AGI What the Master Algorithm truly means — and why we haven’t found it yet Pedro argues that creativity is easy, reliability is hard, and that reasoning by analogy — not just scaling LLMs — may be the key to Einstein-level breakthroughs in AI. Whether you're an AI researcher, machine learning engineer, or just curious about the future of artificial intelligence, this is one of the most important conversations on how to actually reach AGI. 📚 About Pedro Domingos: Pedro is a professor at the University of Washington and author of the bestselling book The Master Algorithm, which explores how the unification of AI's "five tribes" could produce the ultimate learning algorithm. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) The Five Tribes of AI Explained (02:23) The Origins of The Master Algorithm (08:22) Designing with Bit Strings: Radios, Robots & More (10:46) Fitness Functions vs Reward Functions in AI (15:51) What Is Reasoning by Analogy in AI? (18:38) Kernel Machines and Support Vector Machines Explained (22:23) Case-Based Reasoning and Real-World Use Cases (27:38) Are AI Tribes Still Siloed or Finally Collaborating? (32:42) Why AI Needs a Deeply Unified Master Algorithm (36:40) Creativity vs Reliability in AI (39:14) Can AI Achieve Scientific Breakthroughs? (41:26) Why Reasoning by Analogy Is AI’s Missing Link (45:10) Evolutionaries: The Most Distant Tribe in AI (48:41) Will Quantum Computing Help AI Reach AGI? (53:15) Are We Close to the Master Algorithm? (57:44) Tech Leaders, Hype & the Reality of AGI (01:04:06) The AGI Spectrum: Where We Are & What’s Missing (01:06:18) Pedro’s Research Focus
/episode/index/show/aneyeonai/id/36291290
info_outline
#249 Brice Challamel: How Moderna is Using AI to Disrupt Modern Healthcare
04/20/2025
#249 Brice Challamel: How Moderna is Using AI to Disrupt Modern Healthcare
This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved. Offer only for new US customers with a minimum financial commitment. See if you qualify for half off at In this episode of Eye on AI, Craig Smith sits down with Brice Challamel, Head of AI Products and Innovation at Moderna, to explore how one of the world’s leading biotech companies is embedding artificial intelligence across every layer of its business—from drug discovery to regulatory approval. Brice breaks down how Moderna treats AI not just as a tool, but as a utility—much like electricity or the internet—designed to empower every employee and drive innovation at scale. With over 1,800 GPTs in production and thousands of AI solutions running on internal platforms like Compute and MChat, Moderna is redefining what it means to be an AI-native company. Key topics covered in this episode: How Moderna operationalizes AI at scale GenAI as the new interface for machine learning AI’s role in speeding up drug approvals and clinical trials The future of personalized cancer treatment (INT) Moderna’s platform mindset: AI + mRNA = next-gen medicine Collaborating with the FDA using AI-powered systems Don’t forget to like, comment, and subscribe for more interviews at the intersection of AI and innovation. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Preview (02:49) Brice Challamel’s Background and Role at Moderna (05:51) Why AI Is Treated as a Utility at Moderna (09:01) Moderna's AI Infrastructure (11:53) GenAI vs Traditional ML (14:59) Combining mRNA and AI as Dual Platforms (18:15) AI’s Impact on Regulatory & Clinical Acceleration (23:46) The Five Core Applications of AI at Moderna (26:33) How Teams Identify AI Use Cases Across the Business (29:01) Collaborating with the FDA Using AI Tools (33:55) How Moderna Is Personalizing Cancer Treatments (36:59) The Role of GenAI in Medical Care (40:10) Producing Personalized mRNA Medicines (42:33) Why Moderna Doesn’t Sell AI Tools (45:30) The Future: AI and Democratized Biotech
/episode/index/show/aneyeonai/id/36233740
info_outline
#248 Pedro Domingos: How Connectionism Is Reshaping the Future of Machine Learning
04/17/2025
#248 Pedro Domingos: How Connectionism Is Reshaping the Future of Machine Learning
This episode is sponsored by Indeed. Stop struggling to get your job post seen on other job sites. Indeed's Sponsored Jobs help you stand out and hire fast. With Sponsored Jobs your post jumps to the top of the page for your relevant candidates, so you can reach the people you want faster. Get a $75 Sponsored Job Credit to boost your job’s visibility! Claim your offer now: In this episode, renowned AI researcher Pedro Domingos, author of The Master Algorithm, takes us deep into the world of Connectionism—the AI tribe behind neural networks and the deep learning revolution. From the birth of neural networks in the 1940s to the explosive rise of transformers and ChatGPT, Pedro unpacks the history, breakthroughs, and limitations of connectionist AI. Along the way, he explores how supervised learning continues to quietly power today’s most impressive AI systems—and why reinforcement learning and unsupervised learning are still lagging behind. We also dive into: The tribal war between Connectionists and Symbolists The surprising origins of Backpropagation How transformers redefined machine translation Why GANs and generative models exploded (and then faded) The myth of modern reinforcement learning (DeepSeek, RLHF, etc.) The danger of AI research narrowing too soon around one dominant approach Whether you're an AI enthusiast, a machine learning practitioner, or just curious about where intelligence is headed, this episode offers a rare deep dive into the ideological foundations of AI—and what’s coming next. Don’t forget to subscribe for more episodes on AI, data, and the future of tech. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) What Are Generative Models? (03:02) AI Progress and the Local Optimum Trap (06:30) The Five Tribes of AI and Why They Matter (09:07) The Rise of Connectionism (11:14) Rosenblatt’s Perceptron and the First AI Hype Cycle (13:35) Backpropagation: The Algorithm That Changed Everything (19:39) How Backpropagation Actually Works (21:22) AlexNet and the Deep Learning Boom (23:22) Why the Vision Community Resisted Neural Nets (25:39) The Expansion of Deep Learning (28:48) NetTalk and the Baby Steps of Neural Speech (31:24) How Transformers (and Attention) Transformed AI (34:36) Why Attention Solved the Bottleneck in Translation (35:24) The Untold Story of Transformer Invention (38:35) LSTMs vs. Attention: Solving the Vanishing Gradient Problem (42:29) GANs: The Evolutionary Arms Race in AI (48:53) Reinforcement Learning Explained (52:46) Why RL Is Mostly Just Supervised Learning in Disguise (54:35) Where AI Research Should Go Next
/episode/index/show/aneyeonai/id/36206780
info_outline
#247 Barr Moses: Why Reliable Data is Key to Building Good AI Systems
04/13/2025
#247 Barr Moses: Why Reliable Data is Key to Building Good AI Systems
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to to know more. In this episode of Eye on AI, Craig Smith sits down with Barr Moses, Co-Founder & CEO of Monte Carlo, the pioneer of data and AI observability. Together, they explore the hidden force behind every great AI system: reliable, trustworthy data. With AI adoption soaring across industries, companies now face a critical question: Can we trust the data feeding our models? Barr unpacks why data quality is more important than ever, how observability helps detect and resolve data issues, and why clean data—not access to GPT or Claude—is the real competitive moat in AI today. What You’ll Learn in This Episode: Why access to AI models is no longer a competitive advantage How Monte Carlo helps teams monitor complex data estates in real-time The dangers of “data hallucinations” and how to prevent them Real-world examples of data failures and their impact on AI outputs The difference between data observability and explainability Why legacy methods of data review no longer work in an AI-first world Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Intro (01:08) How Monte Carlo Fixed Broken Data (03:08) What Is Data & AI Observability? (05:00) Structured vs Unstructured Data Monitoring (08:48) How Monte Carlo Integrates Across Data Stacks (13:35) Why Clean Data Is the New Competitive Advantage (16:57) How Monte Carlo Uses AI Internally (19:20) 4 Failure Points: Data, Systems, Code, Models (23:08) Can Observability Detect Bias in Data? (26:15) Why Data Quality Needs a Modern Definition (29:22) Explosion of Data Tools & Monte Carlo’s 50+ Integrations (33:18) Data Observability vs Explainability (36:18) Human Evaluation vs Automated Monitoring (39:23) What Monte Carlo Looks Like for Users (46:03) How Fast Can You Deploy Monte Carlo? (51:56) Why Manual Data Checks No Longer Work (53:26) The Future of AI Depends on Trustworthy Data
/episode/index/show/aneyeonai/id/36115930
info_outline
#246 Will Granis: How Google Cloud is Powering the Future of Agentic AI
04/09/2025
#246 Will Granis: How Google Cloud is Powering the Future of Agentic AI
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to What happens when AI agents start negotiating, automating workflows, and rewriting how the enterprise world operates? In this episode of the Eye on AI podcast, Will Grannis, CTO of Google Cloud, reveals how Google is leading the charge into the next frontier of artificial intelligence: agentic AI. From multi-agent systems that can file your expenses to futuristic R2-D2-style assistants in real-time race strategy, this episode dives deep into how AI is no longer just about models—it's about autonomous action. In this episode, we explore: How AgentSpace is transforming how enterprises build AI agents The evolution from rule-based workflows to intelligent orchestration Real-world use cases: expense automation, content creation, code generation Trust, sovereignty, and securing agentic systems at scale The future of multi-agent ecosystems and AI-driven scientific discovery How large enterprises can match startup agility using their data advantage Whether you're a founder, engineer, or enterprise leader—this episode will shift how you think about deploying AI in the real world. Subscribe for more deep dives with tech leaders and AI visionaries. Drop a comment with your thoughts on where agentic AI is headed! (00:00) Preview and Intro (02:34) Will Grannis’ Role at Google Cloud (05:14) Origins of Agentic Workflows at Google (09:10) How Generative AI Changed the Agent Game (12:29) Agents, Tool Access & Trust Infrastructure (14:01) What is Agent Space? (16:30) Creative & Marketing Agents in Action (23:29) Core Components of Building Agents (25:29) Introducing the Agent Garden (28:06) The “Cloud of Connected Agents” Concept (33:53) Solving Agent Quality & Self-Evaluation (37:19) The Future of Autonomous Finance Agents (40:55) How Enterprises Choose Cloud Partners for Agents (43:50) Google Cloud’s Principles in Practice (46:27) Gemini’s Context Power in Cybersecurity (49:50) Robotics and R2D2-Inspired AI Projects (52:39) How to Try Agent Space Yourself
/episode/index/show/aneyeonai/id/36064035
info_outline
#245 Rajat Taneja: Visa's President of Technology Reveals Their $3.3 Billion AI Strategy
04/02/2025
#245 Rajat Taneja: Visa's President of Technology Reveals Their $3.3 Billion AI Strategy
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to Visa’s President of Technology, Rajat Taneja, pulls back the curtain on the $3.3 billion AI transformation powering one of the world’s most trusted financial networks. In this episode, Taneja shares how Visa—a company processing over $16 trillion annually across 300 billion real-time transactions—is leveraging AI not just to stop fraud, but to redefine the future of commerce. From deep neural networks trained on decades of transaction data to generative AI tools powering next-gen agentic systems, Visa has quietly been an AI-first company since the 1990s. Now, with 500+ petabytes of data and 2,900 open APIs, it’s preparing for a future where agents, biometrics, and behavioral signals shape every interaction. Taneja also reveals how Visa’s models can mimic bank decisions in milliseconds, stop enumeration attacks, and even detect fraud based on how you type. This is AI at global scale—with zero room for error. What You’ll Learn in This Episode: How Visa’s $3.3B data platform powers 24/7 AI-driven decisioning The fraud models behind stopping $40 billion in criminal transactions What “agentic commerce” means—and why Visa is betting big on it How Visa uses behavioral biometrics to detect account takeovers Why Visa rebuilt its infrastructure for the AI era—10 years ahead of the curve The role of generative AI, biometric identity, and APIs in the next wave of payments The future of commerce isn’t just cashless—it’s intelligent, autonomous, and trust-driven. If you’re curious about how AI is redefining payments, security, and digital identity at massive scale, this episode is essential viewing. Subscribe for more deep dives into the future of AI, commerce, and innovation. Stay Updated: Craig Smith on X: Eye on A.I. on X: (00:00) Introduction (02:57) Meet Rajat Taneja, Visa’s President of Technology (04:02) Scaling AI for 300 Billion Transactions Annually (05:27) The Models Behind Visa’s Fraud Detection (08:02) Visa’s In-House AI Models vs Open-Source Tools (10:54) Inside Visa’s $3.3B AI Data Platform (12:29) Visa’s Role in E-Commerce Innovation (16:24) Biometrics, Identity & Tokenization at Visa (21:14) Visa’s Vision for AI-Driven Commerce
/episode/index/show/aneyeonai/id/35972265
info_outline
#244 Yoav Shoham on Jamba Models, Maestro and The Future of Enterprise AI
03/27/2025
#244 Yoav Shoham on Jamba Models, Maestro and The Future of Enterprise AI
This episode is sponsored by the DFINITY Foundation. DFINITY Foundation's mission is to develop and contribute technology that enables the Internet Computer (ICP) blockchain and its ecosystem, aiming to shift cloud computing into a fully decentralized state. Find out more at In this episode of Eye on AI, Yoav Shoham, co-founder of AI21 Labs, shares his insights on the evolution of AI, touching on key advancements such as Jamba and Maestro. From the early days of his career to the latest developments in AI systems, Yoav offers a comprehensive look into the future of artificial intelligence. Yoav opens up about his journey in AI, beginning with his academic roots in game theory and logic, followed by his entrepreneurial ventures that led to the creation of AI21 Labs. He explains the founding of AI21 Labs and the company's mission to combine traditional AI approaches with modern deep learning methods, leading to innovations like Jamba—a highly efficient hybrid AI model that’s disrupting the traditional transformer architecture. He also introduces Maestro, AI21’s orchestrator that works with multiple large language models (LLMs) and AI tools to create more reliable, predictable, and efficient systems for enterprises. Yoav discusses how Maestro is tackling real-world challenges in enterprise AI, moving beyond flashy demos to practical, scalable solutions. Throughout the conversation, Yoav emphasizes the limitations of current large language models (LLMs), even those with reasoning capabilities, and explains how AI systems, rather than just pure language models, are becoming the future of AI. He also delves into the philosophical side of AI, discussing whether models truly "understand" and what that means for the future of artificial intelligence. Whether you’re deeply invested in AI research or curious about its applications in business, this episode is filled with valuable insights into the current and future landscape of artificial intelligence. Stay Updated: Craig Smith Twitter: Eye on A.I. Twitter: (00:00) Introduction: The Future of AI Systems (02:33) Yoav’s Journey: From Academia to AI21 Labs (05:57) The Evolution of AI: Symbolic AI and Deep Learning (07:38) Jurassic One: AI21 Labs’ First Language Model (10:39) Jamba: Revolutionizing AI Model Architecture (16:11) Benchmarking AI Models: Challenges and Criticisms (22:18) Reinforcement Learning in AI Models (24:33) The Future of AI: Is Jamba the End of Larger Models? (27:31) Applications of Jamba: Real-World Use Cases in Enterprise (29:56) The Transition to Mass AI Deployment in Enterprises (33:47) Maestro: The Orchestrator of AI Tools and Language Models (36:03) GPT-4.5 and Reasoning Models: Are They the Future of AI? (38:09) Yoav’s Pet Project: The Philosophical Side of AI Understanding (41:27) The Philosophy of AI Understanding (45:32) Explanations and Competence in AI (48:59) Where to Access Jamba and Maestro
/episode/index/show/aneyeonai/id/35885215
info_outline
#243 Greg Osuri: Why the Future of AI Depends on Decentralized Cloud Platforms
03/18/2025
#243 Greg Osuri: Why the Future of AI Depends on Decentralized Cloud Platforms
This episode is sponsored by Indeed. Stop struggling to get your job post seen on other job sites. Indeed's Sponsored Jobs help you stand out and hire fast. With Sponsored Jobs your post jumps to the top of the page for your relevant candidates, so you can reach the people you want faster. Get a $75 Sponsored Job Credit to boost your job’s visibility! Claim your offer now: Greg Osuri’s Vision for Decentralized Cloud Computing | The Future of AI & Web3 Infrastructure The cloud is broken—can decentralization fix it? In this episode, Greg Osuri, founder of Akash Network, shares his groundbreaking approach to decentralized cloud computing and how it's disrupting hyperscalers like AWS, Google Cloud, and Microsoft Azure. Discover how Akash Network’s peer-to-peer marketplace is slashing cloud costs, unlocking unused compute power, and paving the way for AI-driven infrastructure without Big Tech’s control. What You'll Learn in This Episode: - Why AI training is hitting an energy bottleneck and how decentralization solves it - How Akash Network creates a global marketplace for underutilized compute power - The role of blockchain in securing cloud resources and enforcing smart contracts - The privacy risks of hyperscalers—and why sovereign AI in the home is the future - How Akash Network is evolving from a resource marketplace to a full-fledged services economy - The future of AI, energy-efficient cloud solutions, and decentralized infrastructure The battle for the future of cloud computing is on—and decentralization is winning. If you're interested in AI, blockchain, Web3, or the economics of cloud infrastructure, this episode is a must-watch! Stay Updated: Craig Smith Twitter: Eye on A.I. Twitter: (00:00) Introduction & The Biggest Challenges in AI Training (02:36) Greg Osuri’s Background (04:50) The Problem with AWS, Google Cloud & Traditional Cloud Providers (06:40) How To Use Blockchain for a Decentralized Cloud (10:17) Akash Network’s Marketplace Matches Compute Buyers & Sellers (14:42) Security & Privacy: Protecting Users from Data Risks (18:25) The Energy Crisis: Why Hyperscalers Are Unsustainable (21:51) The Future of AI: Decentralized Cloud & Home AI Computing (26:42) How AI Workloads Are Routed & Optimized (30:24) Big Companies Using Akash Network: NVIDIA, Prime Intellect & More (45:49) Building a Decentralized AI Services Marketplace (55:09) Why the Future of AI Needs a Decentralized Cloud
/episode/index/show/aneyeonai/id/35724570
info_outline
#242 Dylan Arena: The AI Education Revolution: How AI is Changing the Way We Learn
03/12/2025
#242 Dylan Arena: The AI Education Revolution: How AI is Changing the Way We Learn
This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking. Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience. Visit extremenetworks.com to learn more. ———————————————————————————————————————— The Role of AI in Education | Dylan Arena on Learning, AI Tutoring & The Future of Teaching How can AI enhance education without replacing the human touch? In this episode, Dylan Arena, Chief Data Science and AI Officer at McGraw Hill, shares his insights on the intersection of AI and learning. Dylan’s background in learning sciences and technology design has shaped his approach to AI-powered tools that help students and teachers—not replace them. He discusses how AI can augment human relationships in education, improve personalized learning, and assist teachers with real-time insights while avoiding the pitfalls of over-reliance on automation. With AI playing an increasingly central role in education, are we at risk of losing the essential human connections that define great learning experiences? What You’ll Learn in This Episode: - Why AI should be used to enhance not replace teachers - The risks and rewards of AI-powered tutoring - How AI-driven assessments can improve personalized learning - Why AI chatbots in education need careful ethical considerations - The future of gamification and AI-driven engagement in classrooms - How McGraw Hill is integrating AI into its learning platforms If you care about the future of education, AI, and ethical tech development, this episode is a must-watch. ———————————————————————————————————————— This episode is sponsored by Oracle. Oracle Cloud Infrastructure (OCI) is a blazing-fast and secure platform for your infrastructure, database, application development, plus all your AI and machine learning workloads. OCI costs 50% less for compute and 80% less for networking—so you’re saving a pile of money. Thousands of businesses have already upgraded to OCI, including MGM Resorts, Specialized Bikes, and Fireworks AI. Cut your current cloud bill in HALF if you move to OCI now: ———————————————————————————————————————— Chapters: (00:00) The Role of AI in Augmenting Human Learning (02:10) Dylan’s Background in Learning Sciences & AI (08:23) The Risks of AI-Powered Education Tools (11:08) AI Tutoring: Can It Replace Human Teachers? (16:28) AI’s Role in Personalized Learning & Adaptive Assessments (22:47) How AI Can Assist, Not Replace, Teachers (29:36) The Future of AI-Driven Gamification in Education (36:41) Ethical Concerns Around AI Chatbots & Student Relationships (45:02) The Impact of AI on Student Learning & Memory Retention (50:19) How McGraw Hill is Innovating with AI in Education (54:44) Final Thoughts: AI’s Role in Shaping the Future of Learning
/episode/index/show/aneyeonai/id/35646615
info_outline
#241 Patrick M. Pilarski: The Alberta Plan’s Roadmap to AI and AGI
03/07/2025
#241 Patrick M. Pilarski: The Alberta Plan’s Roadmap to AI and AGI
This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to to know more. Can AI learn like humans? In this episode, Patrick Pilarski, Canada CIFAR AI Chair and professor at the University of Alberta, breaks down The Alberta Plan—a bold roadmap for achieving Artificial General Intelligence (AGI) through reinforcement learning and real-time experience-based AI. Unlike large pre-trained models that rely on massive datasets, The Alberta Plan champions continual learning, where AI evolves from raw sensory experience, much like a child learning through trial and error. Could this be the key to unlocking true intelligence? Pilarski also shares insights from his groundbreaking work in bionic medicine, where AI-powered prosthetics are transforming human-machine interaction. From neuroprostheses to reinforcement learning-driven robotics, this conversation explores how AI can enhance—not just replace—human intelligence. What You’ll Learn in This Episode: Why reinforcement learning is a better path to AGI than pre-trained models The four core principles of The Alberta Plan and why they matter How AI-driven bionic prosthetics are revolutionizing human-machine integration The battle between reinforcement learning and traditional control systems in robotics Why continual learning is critical for AI to avoid catastrophic forgetting How reinforcement learning is already powering real-world breakthroughs in plasma control, industrial automation, and beyond The future of AI isn’t just about more data—it’s about AI that thinks, adapts, and learns from experience. If you're curious about the next frontier of AI, the rise of reinforcement learning, and the quest for true intelligence, this episode is a must-watch. Subscribe for more AI deep dives! (00:00) The Alberta Plan: A Roadmap to AGI (02:22) Introducing Patrick Pilarski (05:49) Breaking Down The Alberta Plan’s Core Principles (07:46) The Role of Experience-Based Learning in AI (08:40) Reinforcement Learning vs. Pre-Trained Models (12:45) The Relationship Between AI, the Environment, and Learning (16:23) The Power of Reward in AI Decision-Making (18:26) Continual Learning & Avoiding Catastrophic Forgetting (21:57) AI in the Real World: Applications in Fusion, Data Centers & Robotics (27:56) AI Learning Like Humans: The Role of Predictive Models (31:24) Can AI Learn Without Massive Pre-Trained Models? (35:19) Control Theory vs. Reinforcement Learning in Robotics (40:16) The Future of Continual Learning in AI (44:33) Reinforcement Learning in Prosthetics: AI & Human Interaction (50:47) The End Goal of The Alberta Plan
/episode/index/show/aneyeonai/id/35559520
info_outline
#240 Manos Koukoumidis: Why The Future of AI is Open-Source
03/04/2025
#240 Manos Koukoumidis: Why The Future of AI is Open-Source
This episode is brought to you by Sonar, the creators of SonarQube Server, Cloud, IDE, and the open source Community Build. Sonar unlocks actionable code intelligence, helping to redefine the software development lifecycle by use of AI and AI agentic systems, to continuously improve quality and security while reducing developer toil. By analyzing all code, regardless of who writes it—your internal team or genAI—Sonar enables more secure, reliable, and maintainable software. Join the over 7 million developers from organizations like the DoD, Microsoft, NASA, MasterCard, Siemens, and T-Mobile, who use Sonar. Visit to try SonarQube for free today. ———————————————————————————————————————— The Future of AI is Open-Source | Manos Koukoumidis on UMI & The AI Revolution Is closed AI holding back innovation? In this episode, Manos Koukoumidis, CEO of , makes the case for why the future of AI must be open-source. OUMI (Open Universal Machine Intelligence) is redefining how AI is built—offering fully open models, open data, and open collaboration to make AI development more transparent, accessible, and community-driven. Big Tech has dominated AI, but UMI is challenging the status quo by creating a platform where anyone can train, fine-tune, and deploy AI models with just a few commands. Could this be the Linux moment for AI? What You’ll Learn in This Episode: Why open-source AI is the only sustainable path forward The difference between “open-source” AI and true open AI How OUMI enables researchers and enterprises to build better AI models Why Big Tech’s closed AI systems are losing their competitive edge The impact of open AI on healthcare, science, and enterprise innovation The future of AI models—will proprietary AI survive? The AI revolution is happening—and it’s open-source. If you care about the future of AI, innovation, and ethical tech development, this episode is a must-watch. ———————————————————————————————————————— This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to ———————————————————————————————————————— (00:00) The True Meaning of Open-Source AI (02:15) The Open vs. Closed AI Debate (07:54) Why Open AI Models Are Safer (10:34) Defining Open Data (13:21)Beating GPT-4-O with an Open AI Model (16:36) Open AI in Healthcare (19:31) Why Open Models Will Dominate (23:07) How OUMI Makes AI Training Fully Accessible & Reproducible (28:44) UMI’s Collaboration with Universities (32:29) The Shift Toward Open A (36:41) Can We Build Truly Open AI Models from Scratch? (40:20) The Role of Open AI in Eliminating Bias (45:02) Will Open AI Replace Proprietary AI Models? (50:19) How OUMI Works (54:44) The Open AI Revolution Has Begun
/episode/index/show/aneyeonai/id/35528725
info_outline
#239 Tuhin Srivatsa: How Baseten is Disrupting AI Deployment & Scaling in 2025
02/26/2025
#239 Tuhin Srivatsa: How Baseten is Disrupting AI Deployment & Scaling in 2025
This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to ————————————————————————————————————————— AI deployment is broken—can it be fixed? In this episode, Tuhin Srivatsa, CEO & Co-Founder of Baseten, reveals how his company is DISRUPTING AI infrastructure, making it easier, faster, and more cost-effective to deploy and scale AI models in production. As enterprises increasingly turn to open-source AI models and grapple with the high costs and complexity of scaling, Baseten offers a game-changing solution that eliminates bottlenecks and simplifies the process. Discover how Baseten is taking on AWS SageMaker, OpenAI, and cloud-based AI deployment platforms to reshape the future of AI model deployment. What You’ll Learn in This Episode: Why AI deployment & scaling is one of the biggest challenges in 2025 How Baseten enables enterprises to run AI models faster & more efficiently The shift from closed-source to open-source AI models—and why it matters The hidden costs of AI inference & how to optimize for performance Why most AI models fail in production and how to prevent it The future of AI infrastructure: What comes next for scalable AI Whether you’re a machine learning engineer, AI researcher, startup founder, or enterprise leader, this episode is packed with actionable insights to help you scale AI models without the headaches. Don’t miss this conversation on the next era of AI deployment! #AI #ArtificialIntelligence #MachineLearning #Baseten #AIDeployment #AIScaling #Inference #MLInfrastructure #TechPodcast Stay Updated: Craig Smith Twitter: Eye on A.I. Twitter: ————————————————————————————————————————— (00:00) Tuhin Srivatsa’s Journey in AI & Baseten (01:50) What is AI Infrastructure & Why It Matters (03:30) How Baseten Optimizes AI Model Deployment (05:19) Why Most AI Deployments Fail (And How to Fix It) (09:17) The Future of Open-Source AI Models in Enterprise (11:01) How Baseten Automates AI Scaling & Inference (14:12) Why AI Developers Struggle with Cloud-Based AI Tools (18:47) The Real Cost of AI Inference (And How to Reduce It) (20:44) Why AI Scaling is the Biggest Challenge in 2025 (26:55) Can AI Run on Non-NVIDIA Chips? (The Hardware Debate) (31:23) The Future of AI Model Deployment & Inference (37:05) How AI Agents & Reasoning Models Are Changing the Game (40:39) The Truth About AI Hype vs. Reality (45:04) How to Get Started with Baseten (45:48) The Future of AI Infrastructure
/episode/index/show/aneyeonai/id/35436160