Podcast appearances and mentions of Craig Smith

Zendesk went private two weeks before ChatGPT launched, and the moment it came out, it was obvious that customer service would never be the same again. Shashi Upadhyay, head of product, engineering, and AI at Zendesk, joins Craig Smith to explain what the company has built since: a self-improving AI system that doesn't just resolve tickets but learns from every failure, studies what the human did to fix it, and gets measurably better over time. He calls it the resolution learning loop, and for Zendesk's best customers, it's already resolving 70 to 90% of incoming tickets autonomously, up from the 10 to 20% that chatbots managed just a few years ago. The conversation goes deep on the engineering decisions that actually matter: why hallucination is a feature, not a bug, and why the real challenge is knowing exactly when to switch from creative AI to deterministic code; why Zendesk acquired Forethought and what made their approach to going live in days rather than months so valuable; and why, despite all the momentum, Upadhyay estimates we are only about 5% through the adoption of AI in customer service. The bottleneck isn't the technology, it's the change management required to restructure how human and AI workforces operate together. His vision of the end state is striking: personal AI agents talking directly to enterprise AI agents, resolving 90% of issues instantly, while humans focus exclusively on the complex, high-value interactions that genuinely require them. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

In this episode of The Brad Jensen Show, Craig Smith and I sit down for a candid conversation about life, growth, and the importance of taking risks. We discuss Craig's decision to step into a new career opportunity, the fear and uncertainty that come with major life changes, and why so many people never give themselves the chance to see what's possible because they're unwilling to bet on themselves. This wasn't a structured episode with one main topic. Just two friends talking shop, sharing lessons, and exploring what it means to pursue growth even when it's uncomfortable. If you've ever felt stuck, scared to make a move, or needed a reminder to trust yourself, you'll enjoy this conversation.   Next Level Links: Work With a Nutrition Coach - Schedule A Consultation Nutrition Coaching - www.becomenextlevel.com   Partner Links: Try Thrive Lab Free For One Month - Start Here Order Supplements From Transform - Shop Here Order Supplements From Cured Nutrition - Shop Here Order Supplements From Legion (use code keynutrition for 20% off first order) - Shop Here   Be Featured on the Show: Apply to be a live calller guest on the show - Submit Application Here Submit Q&A Questions to be read live on the show - Submit Here   Free Guides: Eating Out Guide - Get The Guide High-Protein Fast Food Orders - Get the Guide Macro Food Options Guide - Get The Guide Join Us On Patreon - Join Here   Connect with us on Instagram: Host Brad Jensen – @thesoberbodybuilder Co-Host Craig Smith - @greatestdaymindset Next Level Nutrition – @mynextlevelnutrition

Have you ever found yourself somewhere you never planned to be and wondered, "How did I get here?" This week on Continuing the Conversation, Craig Smith and Abbey Davis dive deeper into the story of Jacob's famous dream and explore one of the most powerful themes in Scripture: God's grace comes to us long before we deserve it. As Jacob runs from the consequences of his own choices, God meets him in an unexpected place with an unexpected promise. Craig and Abby unpack the meaning behind Jacob's ladder, why grace is always God-initiated, and what it means to trust God's direction when life feels uncertain. In this episode, you'll discover: What Jacob's ladder actually represents Why Christianity is different from every other "stairway to heaven" How God's grace reaches us before we reach Him The subtle ways selfishness blocks our relationship with God Why Christians often struggle to celebrate grace in other people How spiritual growth changes the way we see others If you've ever wrestled with disappointment, consequences, comparison, or wondering where God is leading you, this conversation offers hope, perspective, and practical encouragement.

Hi All Here is the podcast of my 'In The Groove' show on Starpoint Radio on Sunday 7th June 2026 featuring new releases by Wez Whynt Ft Hannah Khemoh, Down To The Bone, Pat Bedeau With Sofia Rubina & Rona Ray, Mothers Favorite Child, Delano Smith Ft Ash Lauren, Craig Smith, Cornell CC Carter, Deep Just Ft Evolv Supreem, Alicia Waller and Piers Kirwan Ft Jeremy Glenn, plus vintage grooves from Mike T and Peabo Bryson (R.I.P.) as well as 'A Touch Of Jazz' from MFSB and Dexter Wansel (R.I.P.).. all in 2 hours of fab music, enjoy the selections xPaul Stuart 'In The Groove' - Starpoint Radio - Sunday 7th June 202601. Georgie B & The Groove Association - You Know (Summer Vibes Mix) (Single - georgiebmusic.com 2026)02. Down To The Bone - Feel So Good (Ft Natasha Watts) (This Way Forward LP - Down To The Bone 2026)03. William Richardson - More and More (Ft Harrix) (Single - RLW Productions 2026)04. Gina Sedman - Giving It Back (Who's Clyde LP - ginasedman.bandcamp.com 2026)05. Cornell CC Carter - Let's Get Away From Here (Single - Expansion 2026)06. Peabo Bryson - Paradise (Paradise LP - Capitol 1980)07. Mothers Favorite Child - Bait (Ft Saeeda Wright) (Opolopo Remix) (Dance-Funk-RnB EP - mothersfavoritechild.bandcamp.com 2026)08. MFSB - Mysteries Of The World (Philly Int 12" 1981)09. Alicia Waller - Tempo 120 (Louder, Then LP - Frente/Missing Piece 2026)10. Johnny Britt - You Are Beautiful (R&B Mix) (J-Jams 2026)11. Queen B Unlimited - 27 Sided (Special 45 Version) (Single - Z Records 2026)12. Mothers Favorite Child - You Ain't Riding With Me (Ft Morris Alan) (Opolopo Remix) (Dance-Funk-RnB EP - mothersfavoritechild.bandcamp.com 2026)13. Craig Smith - Gathering Storm (Original Mix) (Single - beyondtomorrowmusic.bandcamp.com 2026)14. Mike T - Do It Any Way You Wanna (Golden Pyramid 12" 1981)15. Prefix One Ft Nambi - Grateful (Glenn Underground Cosmic Disco LoFiJourney Mix)(Househead London 2026)16. Deep Just Ft Evolv Supreem - A Swé A (Tonight) (Josh Milan's Main Mix) (Honeycomb Music 2026)17. Sean Khan Ft Omar - Give Love (Visions 2026)18. Wez Whynt Ft Hannah Khemoh, Lukamusic - Take Me (Main Mix) (Steady Progression Recordings 2026)19. Piers Kirwan Ft Jeremy Glenn - Way Up (Black Sonix Remix) (Boogie Cafe 2026)20. Delano Smith Ft Ash Lauren - Detroit Deep (Kai Alce Remix) (delanosmith.bandcamp.com 2026)21. Stephane Attias Ft Trinidadian Deep - Mother (Visions 2026)22. Ralph Session Ft Brandon Markell Holmes - Everything (Freerange 2026)23. Sonic Soul Orchestra Ft Mishell Ivon - One Love (N.W.N Extended Remix)(King Street 2026)24. Pat Bedeau With Sofia Rubina & Rona Ray - Let It Begin (Extended Mix) (Bedfunk 2026)25. Cafe 432 Ft Wendy Harriott - Good Thing (Extended)(Soundstate Sessions 2026)

You got what you wanted and lost everything that mattered. Now you're alone in a place you never chose. But Jacob's story in Genesis 28 reveals something you need to hear: you're not as lost as you think. God doesn't wait for you to have it together. He meets you right there.

CapeTalk’s Sara-Jayne Makwala King is joined on Weekend Breakfast by Craig Smith, Senior technical marine specialist with WWF South Africa. Weekend Breakfast with Sara-Jayne Makwala King is the weekend breakfast show on CapeTalk. This 3-hour morning programme is the perfect (and perky!) way to kickstart your weekend. Author and journalist Sara-Jayne Makwala-King spends 3 hours interviewing a variety of guests about all things cultural and entertaining. The team keeps an eye on weekend news stories, but the focus remains on relaxation and restoration. Favourites include the weekly wellness check-in on Saturdays at 7:35am and heartfelt chats during the Sunday 9am profile interview. Listen live on Primedia+ Saturdays and Sundays between 07:00 and 10:00am (SA Time) to Weekend Breakfast with Sara-Jayne Makwala-King broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/AgPbZi9 or find all the catch-up podcasts here https://buff.ly/j1EhEkZ Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

AI agents can now connect to every tool your employees use. The problem is that connecting them and trusting them are two completely different things, and most enterprises have figured out the first without solving the second. Oren Michaels, co-founder and CEO of Barndoor AI, joins Craig Smith to explain why that gap is the defining challenge of the agentic enterprise era. His framework is simple and sharp: agents are like enthusiastic interns. They will absolutely do something when you ask them to. Whether it's what you intended is another matter, and when an agent can act across Salesforce, Slack, email, and calendar simultaneously, the blast radius of a misunderstood instruction is far larger than anything a human intern could cause. The conversation covers the 100,000 agent problem - the reality that each agent handling a discrete task needs its own set of rules about what it's allowed to do, and that number scales to a size no human team can govern manually - and why traditional identity management systems were never built for the failure modes AI agents create. The new threat isn't bad actors getting in; it's authorized people using allowed tools with agents that still do the wrong thing. Barn Door's governance layer sits between the agent and the tools it can access, specifying exactly what each agent is permitted to do in each context, and Venn brings that same capability to individuals who want to understand what's possible before their organizations catch up. This is one of the most practically useful conversations available about what enterprise AI governance actually looks like. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Every time you hit a phone tree or a chatbot with canned answers, you're experiencing the gap between what AI can already do and what most companies are still delivering. Craig Smith sits down with Tom Chen, Chief Product Officer at Aircall, to explore why that gap is closing fast, and what it means for any business that relies on voice as a customer communication channel. Tom makes a case that is both practical and counterintuitive: AI voice agents aren't better than your best human rep, but they are better than your average one. They never get frustrated. Their patience is infinite. Their tone never changes. And they can handle 100 concurrent calls at a fraction of the cost of a human operation, without lunch breaks, without bad days, and without going off script. The conversation covers a finding that should change how any business thinks about AI adoption: when one of Aircall's customers gave callers the explicit choice between a human agent and a faster AI agent, far more people chose the AI than anyone expected, and satisfaction scores went up. Tom also identifies the real bottleneck that most businesses don't see coming: it's not the AI technology, which is increasingly commoditized. It's the tribal knowledge, the undocumented expertise that lives in the heads of long-tenured employees and never gets captured anywhere, that determines whether an AI agent performs well or not. Until that knowledge is surfaced, even the best voice agent will underperform. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

What if one of the biggest obstacles to God's blessing in your life is the belief that you need to become someone else first? In this episode of Continuing the Conversation, Craig Smith and Tanner Lowe dive deeper into the story of Isaac, Jacob, and Esau from the Bad Blood series. Together, they explore a surprising truth hidden within one of the Bible's most dysfunctional family stories: God's plan often conflicts with our preferences. Through a fascinating discussion on biblical interpretation, spiritual formation, and leadership, Craig unpacks why Isaac's passivity created ripple effects that impacted generations—and what that means for us today. In this conversation, you'll discover: Why God's plan and our preferences often collide The surprising role Isaac plays in the Jacob and Esau story How spiritual passivity affects the people around us Why following Jesus is about more than personal faith How God shapes our desires over time The difference between God's plan and God's purpose for your life If you've ever struggled to trust God's direction, wondered whether you're missing something He has for you, or felt pressure to become someone you're not, this episode offers practical wisdom and powerful encouragement.

Most AI systems follow a gradient, a mathematical slope that tells them exactly how to improve, step by step, toward a known goal. Neuroevolution doesn't follow any gradient. Instead, it runs hundreds or thousands of competing solutions simultaneously, spreads them across the space of possibilities as broadly as possible, and lets the best ones recombine, the same logic that drives biological evolution. The result, as Risto Miikkulainen explains to Craig Smith, is creativity: solutions that no human designer would have anticipated, that emerge routinely from the evolutionary process. Miikkulainen is a professor at UT Austin and VP of AI Research at Cognizant AI Labs, and he has been working on this field since the 1980s, which makes him both a historian of it and one of its most active frontiersmen. The conversation covers a remarkable range: a mystery model that outperformed every competitor in a recent stock trading competition with forensic footprints pointing to neuroevolutionary AI; Sakana AI's system that autonomously designed experiments, wrote a paper, and had it accepted at a major machine learning conference; and a pandemic decision system that trained overnight and made country-specific recommendations by morning, with Iceland actually following some of them, all the way to the prime minister. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

One in four people over 65 will experience a fall, and for most of them, the technology designed to help is a device that hasn't meaningfully changed since the 1980s. Chia-Lin Simmons, CEO of LogicMark, joined Craig Smith to make the case that this gap is both unnecessary and solvable, and that AI is finally making it possible to shift personal safety from reactive to predictive. Her company's Freedom Alert Max doesn't just detect falls after they happen, it builds a personalized digital twin of each user, tracking steps, sleep patterns, and medication adherence over time to identify the subtle signs of health decline that even daily caregivers often miss. The conversation is one of the most grounded and human discussions of applied AI you'll hear, covering why Apple Watch fall detection was engineered for crash detection, not elderly falls; why AI can flag a problem but a human needs to hear the breathing on the other end of the line; and why the 700,000 caregiver shortage in America makes technology like this not a luxury but a scaling mechanism. For anyone navigating aging parents, their own future, or the sandwich generation pressures in between, this episode is both practically useful and genuinely moving. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Have you ever felt like you had to perform, pretend, or become someone else to earn approval from people, or even from God? This week we dig into one of the Bible's most dysfunctional family stories and discover that the blessing was never meant to be faked for.

Luiz Domingos has spent 25 years watching enterprise communications evolve, from IP telephony to cloud to AI, and his assessment of where things stand now is unusually concrete. Companies have moved past the strategy deck phase. AI is being embedded directly into contact centers, compliance workflows, and communication pipelines, and the question executives are asking has shifted from "which model is smartest" to "which deployment reduces friction and stays compliant." Domingos is direct about what gets in the way: you cannot pour AI into a legacy architecture and expect transformation, and cloud-only AI doesn't solve the latency or data sovereignty problems that regulated industries face every day. In this conversation with Craig Smith, Domingos covers the practical mechanics of how Mitel is applying AI across its portfolio, from real-time transcription and sentiment analytics in contact centers, to agentic workflows that turn conversations into automated tickets and follow-ups. He draws a clear line between AI agents (which give recommendations) and agentic AI (which takes actions), a distinction the market consistently confuses. He also makes a prediction worth noting: within five years, voice will replace the traditional app interface as the primary way people interact with enterprise AI systems. For any CIO or CTO trying to move from experimentation to real ROI, his framework - start with workflow friction, not pilots - is the most actionable takeaway in the episode.

Your child's data profile doesn't start when they get their first phone. It starts before they're born, the moment a parent emails a gynecologist or visits a fertility clinic website. That's the core argument behind Born Private, Proton's new initiative that lets parents reserve an email address for their child at birth, anchoring their digital identity in a privacy-preserving ecosystem before the profiling machine gets started. Craig Smith sits down with Eamonn Maguire, Engineering Director, Machine Learning & AI at Proton, who has spent his career at the intersection of data, security, and visualization to explore what's really happening to our data and what, if anything, we can do about it. The conversation covers the mechanics of how just three email sign-ups can allow Google to infer your age, politics, and religion; why OpenAI and Anthropic have shown "not much regard for the law" when it comes to training data and copyright; and why social media platforms are operating like unregulated gambling companies - engineering addiction with no structural incentive to stop. It's one of the most grounded, specific, and genuinely alarming conversations about digital privacy you'll hear, and it ends with a simple, actionable proposition: privacy should be a decision you make at birth, not a problem you try to solve after the damage is done. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

A fly with 100,000 neurons can fly, find food, and reproduce. A $100 million supercomputer cannot. Dr. Terry Sejnowski used that observation to silence a room full of MIT AI researchers in the 1980s, and it remains just as sharp today. Sejnowski is one of the foundational figures in the history of deep learning, co-inventor of the Boltzmann machine, and a professor at the Salk Institute who has spent his career studying both the brain and the machines we build to imitate it. In this conversation with Craig Smith, he turns that dual perspective on ChatGPT, and what he finds is something genuinely clarifying: not a human mind, not a threat to humanity, but an alien intelligence that has absorbed more knowledge than any brain ever could while remaining fundamentally empty when nobody is talking to it. The conversation covers the full landscape of what current AI is missing - from goals and reinforcement learning to the constant self-generated flow of thought that defines consciousness - and why the word "understanding" is so ambiguous that even the world's top cognitive scientists can't agree on whether ChatGPT has it. Sejnowski also makes the case that hallucinations aren't a flaw to be engineered away but the flip side of creativity itself, that we are in a pre-Copernican era when it comes to understanding intelligence, and that the real future of AI lies not in scaling language models further but in looking at what nature has already solved, from field mice to fruit flies. His new book is written for the general public and available now. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Training a frontier AI model today requires hundreds of thousands of GPUs, months of compute time, and a budget that only a handful of companies on earth can afford. Steffen Cruz, co-founder and CTO of Macrocosmos, thinks that model is about to break, and he's spending his time building what comes next. His project IOTA, operating within the BitTensor blockchain ecosystem, uses distributed training to split large language models across thousands of devices located around the world, coordinated by blockchain, and powered by surplus cheap energy wherever it exists. After nine months of research, the system can reproduce baseline benchmark performance using what Cruz calls "wonky vegetables" - unreliable, churning, globally distributed compute - and turn it into something indistinguishable from centralized training if you use the right approach. The conversation with Craig Smith covers the mechanics of how this actually works, why the blockchain's role is far narrower and more practical than most people assume, and why the Mac mini stockpiling trend creates an unexpected supply of distributed compute that can earn passive income when idle. Cruz's target: a 70 billion parameter model by mid-2025, trained at 10-20% of what it would cost through a hyperscaler, and aimed squarely at the legal firms, hospitals, and cash-strapped startups that have been waiting to train their own sovereign models but couldn't afford the price tag. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Errol Gardner has spent 35 years advising the world's largest organizations through major technology transitions, and his assessment of where enterprise agentic AI actually stands is one of the most grounded you'll hear anywhere. His number: less than 1 out of 10 on a maturity scale. Not because the technology isn't ready, but because deploying agentic AI across an organization doesn't tweak how it works, it requires rebuilding how it works. And that is a fundamentally different kind of challenge than anything the AI hype cycle is currently acknowledging. In this conversation with Craig Smith, Gardner walks through why cloud adoption still hasn't reached 7 out of 10, what that means for agentic AI timelines, why the single biggest barrier to adoption is human resistance rather than technical limitation, and why governments will ultimately have to step in to manage workforce displacement at scale. He also raises a question that almost nobody is asking: is the value exchange between the technology sector and traditional industries sustainable in the long run? It's a conversation that doesn't just describe where AI is, it explains why the gap between the narrative and the reality has never been wider. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

Family tension. Generational mistakes. Repeating the same patterns over and over again. In this episode of Continuing the Conversation, Craig Smith and Colin McFarland dive deeper into Genesis and unpack the surprising purpose behind biblical history. Is the Bible just recording events… or is it trying to reshape how we see the world? From Jacob and Esau to Isaac's passivity, this conversation explores how unhealthy patterns get passed down through generations—and why God keeps inviting people into something different. You'll hear: Why Genesis is more than a history book How worldview formation shapes our lives today The hidden dysfunction underneath the Jacob and Esau story Why "following Jesus" is different than simply "knowing the Bible" How generational patterns continue unless someone breaks them This episode is honest, insightful, practical, and deeply relevant if you've ever looked at your family history and thought, "I don't want to repeat this anymore."

IBM's VP of Quantum Systems, Oliver Dial, has spent his career building quantum computers from the ground up, and he's unusually direct about what they can and can't do. In this conversation with Craig Smith, Oliver Dial walks through where the field actually stands in 2026: quantum utility was achieved in 2023, quantum advantage is the target for this year, and a fully error-corrected machine capable of tackling the hard problems is on IBM's roadmap for 2029. That last milestone, Dial says, now feels both achievable and terrifying. The episode is worth your time because Dial doesn't hype. He explains why IBM built a 1,000-qubit computer and then took it apart almost immediately, why Google's quantum advantage claims remain scientifically contested, and how a new error-correcting code IBM developed just reduced the qubit overhead required for fault-tolerant quantum computing by an order of magnitude. For anyone trying to understand what quantum computing will actually mean for their industry, and when, this is the clearest map of the road ahead available right now. If this conversation changed how you think about the future of computing, subscribe to Eye on A.I. for weekly conversations with the researchers and builders shaping what comes next.

Esau didn't lose his birthright because it was taken, he traded it away because he was in a hurry. Find out what his story reveals about the blessings we're missing in our own lives.

Feeling exhausted? Overwhelmed? Like you're running on empty no matter how hard you try? In this powerful message from Isaiah 40:27–31, Pastor Craig Smith shares a hope-filled truth for anyone tired of just surviving. God never intended for you to carry life's weight alone—and He offers something better than grit, hustle, or trying harder. This message explores: Why overwhelm can make us feel forgotten by God The difference between a calling and a craving Why some of us are exhausted from running in the wrong direction How God renews strength for those who trust Him What it looks like to run without growing weary If you've been spiritually, emotionally, or mentally drained, this message is an invitation to slow down, refocus, and discover the strength only God can provide. Your exhaustion doesn't have to define you. There's hope. There's rest. And there's a better way forward.

Kris Lovejoy, Global Strategy Leader at Kyndryl, has spent her career at the intersection of IT infrastructure and security. Right now, she's one of the people enterprises call when they want to move from AI experimentation to real deployment. Her diagnosis is clear: agentic AI is a bullet train sitting on tracks built for 30 miles per hour. The technology is ready. Most organizations aren't, and the gap between a successful pilot and a production system running at scale is far wider than the hype suggests. In this conversation with Craig Smith, Lovejoy walks through why IT service management is the smartest entry point for agentic adoption, how cost savings of up to 90% in that area can fund broader modernization, and why the security risks in agentic systems are less about sophisticated hackers and more about misconfiguration, bad context, and human error. She closes with a specific prediction: half of traditional IT administration tasks will be handled by AI agents by 2031, and a surprising take on who will actually thrive in the agentic era: not coders, but people trained to ask the right questions. For anyone making decisions about AI adoption, this is the most practical conversation available right now. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.

In this episode, Chris O'Donnell, the President of Select Service Division at Aimbridge Hospitality, shares how the balanced scorecard turns hotel operations into a meritocracy. You'll hear how Aimbridge cascades five universal metrics from CEO Craig Smith down to every property, why turnaround success starts with quick wins, and the bias-for-action principle Chris carries into every problem. A few more resources:If you're new to Hospitality Daily, start here. You can send me a message here with questions, comments, or guest suggestionsIf you want to get my summary and actionable insights from each episode delivered to your inbox each day, subscribe here for free.Follow Hospitality Daily and join the conversation on YouTube, LinkedIn, and Instagram.If you want to advertise on Hospitality Daily, here are the ways we can work together.If you found this episode interesting or helpful, send it to someone on your team so you can turn the ideas into action and benefit your business and the people you serve!Music for this show is produced by Clay Bassford of Bespoke Sound: Music Identity Design for Hospitality Brands

Economists and politicians have turned him into a mascot for free-market ideology. Some on the left say the right has badly misread him. In this updated replay of a 2022 episode, we hold a very Smithy tug of war.   SOURCES: Eamonn Butler, co-founder and director of the Adam Smith Institute. Glory Liu, a political scientist and Adam Smith scholar at Georgetown University. Mariana Mazzucato, professor in the economics of innovation and public value at University College London. Dennis Rasmussen, a professor of political science at Syracuse University. Russ Roberts, president of Shalem College in in Jerusalem; host of the EconTalk podcast; and author. Craig Smith, Adam Smith Senior Lecturer in the Scottish Enlightenment at the University of Glasgow.   RESOURCES: Adam Smith's America: How a Scottish Philosopher Became an Icon of American Capitalism, by Gloria Liu (2022). "Henry and Adam: A Deep and Special Friendship," by Benny Higgins (Adam Smith Panmure House Perspective, 2020). "Rescuing Adam Smith From Myth and Misrepresentation," (The Economist, 2018). The Infidel and the Professor: David Hume, Adam Smith, and the Friendship That Shaped Modern Thought, by Dennis C. Rasmussen (2017). How Adam Smith Can Change Your Life: An Unexpected Guide to Human Nature and Happiness, by Russ Roberts (2014). "British Privatization — Taking Capitalism to the People," by John Moore (Harvard Business Review, 1992). Free to Choose: A Personal Statement, by Milton Friedman and Rose Friedman (1990). The Essential Adam Smith, edited by Robert L. Heilbroner (1986). An Inquiry into the Nature and Causes of the Wealth of Nations, by Adam Smith (1776). The Theory of Moral Sentiments, by Adam Smith (1759).   EXTRAS: "In Search of the Real Adam Smith," series by Freakonomics Radio (2022). Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ever feel overwhelmed by life… like your problems are just too big? What if the issue isn't the size of your problems—but the way you see them? In this episode of Continuing the Conversation, Craig Smith and Colin McFarland unpack a powerful mindset shift from the Overcoming Overwhelmed series. They explore what it means to make God your "big hammer"—and how reframing your challenges through faith can move you from anxiety to anticipation. You'll hear: Why your perspective matters more than your situation A simple daily question that can reshape your thinking How God works through every situation—even the hard ones Why our understanding of God is often too small How to trust God when you can't fully understand Him If Sunday's message left you thinking, this conversation will help you take the next step.

Feeling overwhelmed? You're not alone—and you're not stuck. In this message from our Overcoming Overwhelm series, we explore a powerful truth: it's not the size of your problems that's crushing you—it's the size of your perspective. Through Isaiah 40, we're reminded that nothing compares to God. Not your stress. Not your fear. Not the weight you've been carrying. When life gets loud and heavy, it's easy to focus on what's right in front of you. But what if the answer isn't fixing your problems… but lifting your eyes? This message will help you: Reframe what's overwhelming you Recognize what you've been leaning on instead of God Take a practical step to bring God back into focus You don't need smaller problems. You need a bigger view of God.

AI has fundamentally changed the cybersecurity threat landscape, not by inventing new attack types, but by collapsing the timeline. The same tools that make software developers more productive are now being used by attackers to move from vulnerability disclosure to active exploit in a matter of hours. That shift, argues Loris Degioanni, CTO and founder of Sysdig, changes everything about how defense needs to work. In this episode, Craig Smith talks with Loris Degioanni about why human-centered security is becoming a structural liability, what "headless cloud security" means in practice, and why the coding agent (tools like Claude Code or Codex) may become the new operating system through which all enterprise security workflows run. It's a conversation about architecture, urgency, and what it actually means to fight a tank when you've been trained to use a baseball bat. If this conversation made you think differently about AI and security, subscribe to Eye on A.I. for weekly conversations with the people building and defending the future.

 Special guest interviewee this month is Craig Smith, joining Pete to tell all about his pre 1980s Star Wars collecting. Elsewhere the lads indulge in a little fantasy theme park fun, tell all about their latest finds with even Richard picking something up this month, and go international as Face-Off heads to Spain, Canada, Mexico and, err, Indonesia. Andy Preston takes the reigns as quizmaster, and the team picks the best new acquisitions from around the world, with a DT Ben, an prototype poster, a Vader / Chewie mix-up, soapy Star Wars and Italian stationery. In Rebel Briefings the boys look back at Live, selling See Threepio, modelling on Endor, Maul on telly, Japanese rocket robots, Vic Reeves paintwork, and Youngie Oldie Yoda. Licensee this month is Kenner's pre-school range, from Star Tots to talking telephones, and all things Ewok - Fire Cart, Family Hut, Woodland Wagon and more. A lesser known, and - maybe - under rated line? Find out more on the podcast! Plenty of bluster and banter alongside, you can find the podcast in all the usual places.

What if the most competitive exam in the world is also the most destructive? In this episode of Eye on AI, Craig Smith sits down with Professor Andrew Thangaraj, faculty at the Department of Electrical Engineering at IIT Madras, to explore how one of India's most prestigious institutions is quietly dismantling the system it helped build. Andrew lays out the honest reality of higher education in India. Two and a half crore kids reach college age every year. Only 90 lakh make it to college. And the IITs, the most coveted institutions in the country, take just 17,000. The competition to reach those seats has become so extreme that students are losing their childhoods, their development is stunted, and even those who make it through are often unemployable because the system rewards knowledge over skills. Andrew walks through exactly how IIT Madras is responding. A full, IIT-branded undergraduate degree in data science delivered entirely online for under five lakhs, roughly $5,000. No JEE required. No elite school background needed. Just a 10th standard foundation and the willingness to do the work. The program flips the traditional model, putting hands-on skills and real projects before theory, building in multiple exit points for students who need to start earning before they finish, and scaling to over 40,000 active students through a hybrid of faculty-recorded lectures, full-time instructors, and a remarkably active student community. We also get into the bigger picture. Why India's AI talent gap is as much a culture problem as a numbers problem. Whether India can leapfrog into AI leadership the way China did after rebuilding its research ecosystem. Where AI tools are already being tested inside the program and where they still fall short. And how AI deployed in Indian languages, in agriculture, and in the courts could drive the kind of societal change that no corporate productivity tool ever will.  Subscribe for more conversations with the people shaping the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) Introduction and Andrew Thangaraj's Background (01:29) India's Higher Education Bottleneck (03:45) Designing a $5,000 IIT Degree  (09:27) Why Graduates Still Lack Skills (12:31) When the Program Started and How It Got Approved (13:56) Program Structure, Diplomas and Multiple Exit Points (17:52) Who the Program Reaches and Surprising Student Stories (24:57) Older Students, Working Professionals and International Enrollment (29:55) Can India Leapfrog in AI (34:03) Data Centers, Power and Infrastructure Gaps  (40:57) How Involved Are the IITs in India's AI Mission (46:00) AI for Languages, Farms and Courts

What does the quantum industry actually look like right now, beneath all the hype? In this episode of Eye on AI, Craig Smith sits down with Celia Merzbacher, Executive Director of the Quantum Economic Development Consortium (QED-C), to break down the real state of quantum technology in 2025. From market growth and enterprise readiness to the growing intersection with AI, Celia brings a grounded insider perspective on where the industry stands and what comes next. Celia explains why the quantum market is growing faster than even the companies inside it predicted, with revenues rising roughly 27% year over year and actual numbers consistently beating forecasts. She also makes clear that the future is not quantum replacing classical computers. It is hybrid systems combining both to solve problems that simply cannot be solved today, with early use cases already emerging in pharmaceuticals, energy, finance, and defense.  We also get into quantum sensing, the most underrated corner of the quantum world. From biomedical imaging already in clinical trials to quantum clocks powering GPS and financial transaction timestamping, sensing is already partially commercialized and quietly reshaping industries most people have never connected to quantum at all. Finally, Celia addresses the AI question directly. Will AI replace quantum? No. The two are complementary. AI is already accelerating quantum hardware design and algorithm discovery, and quantum may eventually improve how AI systems are trained. She closes with a clear message for enterprise leaders: the transition to quantum will not be a migration. It will be a paradigm shift, and the time to start preparing is now.  Subscribe for more conversations with the people building the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   Timestamp: (00:00) Introduction: What Is QED-C and Why Does It Exist? (01:57) Celia Merzbacher on Her Background and Role (04:32) Annual Market Survey: How Fast Is Quantum Actually Growing? (09:10) Where Quantum Revenue Is Coming From Today (11:11) Timeline and the Race to Utility-Scale Quantum Computing (13:23) Early Use Cases: Pharma, Energy, Finance and Hybrid Computing (16:14) What Is Quantum Sensing and Why It Matters (20:39) The Three Pillars: Hardware, Error Correction and Algorithms (27:40) How Enterprises Should Start Preparing for Quantum Now (38:39) AI and Quantum: Allies Not Competitors

What if you could train a frontier AI model without building a single data centre? In this episode of Eye on AI, Craig Smith sits down with Steffen Cruz, co-founder and CTO of Macrocosmos, to explore a radical alternative to the way AI models are built today. Instead of billion-dollar GPU warehouses, Steffen is training large language models using idle compute from devices distributed around the world, coordinated through the Bittensor blockchain. Steffen breaks down why the centralised data centre model is heading toward a wall. Projects like Stargate and Colossus cost tens of billions of dollars, and as appetite for larger models grows, the economics simply stop making sense. He explains how distributed training flips this on its head, tapping into surplus energy, underutilised GPUs, and even consumer devices like Mac Minis to train models at a fraction of the cost. We also get into IOTA, Macrocosmos's flagship technology, an orchestration layer that takes compute nodes scattered across the globe and makes them act like a single supercomputer. No single device runs the full model. Instead, each one carries a small slice, a technique called model parallelism, and together they can train frontier-scale models that would otherwise be out of reach for startups, researchers, and enterprises. Finally, Steffen shares what he's building toward: 70 billion parameter models trained at 10 to 20 percent of centralised costs, a two-sided marketplace for compute, and a future where anyone with a spare GPU or Mac Mini can earn passive income while contributing to the democratisation of AI. Subscribe for more conversations with the people building the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   Timestamp: (00:00) Introduction: The Problem With Blockchain AI Projects (06:39) Meet Steffen Cruz: From Subatomic Physics to Decentralised AI (09:16) What Is a Bittensor? The Blockchain Built for AI (11:53) How the Blockchain Actually Works: Registry, Clock, and Rewards (15:08) Why Data Centres Are Hitting a Wall (22:01) Distributed Training vs Federated Learning: What's the Difference? (27:47) Train at Home: Turning Your Mac Mini Into a Passive Income Machine (32:49) IOTA Explained: Building a Global Supercomputer From Spare Parts (39:43) How the Network Scales: From 256 Nodes to Limitless Compute (44:39) The Road Ahead: 70B Parameter Models and the Future of Affordable A

What if your child already has a data profile, and they haven't even been born yet? In this episode of Eye on AI, Craig Smith sits down with Eamonn Maguire, Director of Engineering for AI and ML at Proton, to explore one of the most urgent and underappreciated questions in the age of AI: who owns your data, who is building a profile on you, and what can actually be done about it? Eamonn brings a rare combination of depth and range to this conversation. With a PhD from Oxford, a postdoc at CERN, and years at Facebook engineering ML systems to detect internal and external threats, he now leads Proton's AI efforts, including Lumo, their end-to-end encrypted alternative to ChatGPT. He makes a compelling case that the surveillance economy is not just a privacy problem but a behavioral one, where the systems profiling you are not only observing who you are but actively shaping who you become. We get into how just three data points are enough for advertisers to infer your age, political leanings, religion, and spending habits. We discuss why trusting mainstream AI platforms with sensitive data is a structural problem, not just a policy one, and why the AI labs with the best models got there by acquiring the most data, often with little regard for copyright law. Eamonn also breaks down the difference between truly open models and open washing, and explains how Proton builds AI that is genuinely private by design, with local indexing, encrypted memory, and user-controlled data sharing. Then there is Born Private, Proton's initiative to give children a private digital identity from birth. It sounds simple on the surface, but the conversation it opens up is anything but. Data collection on your child begins before they are born, the moment a parent emails a gynecologist or a fertility clinic. Eamonn argues that until we start thinking about privacy the way we think about other rights, from the very beginning, the surveillance machine will always have a head start. Subscribe for more conversations with the people building the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on AI on X: https://x.com/EyeOn_AI   Timestamp: (00:00) Introduction and Meet Eamonn Maguire (00:38) From Bioinformatics to CERN to Facebook: Eamonn's Career Arc (05:23) How Proton Started in the CERN Cafeteria (09:23) What Mainstream AI Platforms Actually Do With Your Data (13:00) Copyright, Training Data, and Why Big Labs Can't Be Trusted (15:10) Open Models vs Open Washing: What Truly Open AI Looks Like (24:22) How Lumo Works: Encrypted Memory and No Data Leakage (31:18) Born Private: Reserving a Private Email Address at Birth (33:00) How Data Profiling Starts Before Your Child Is Born (34:26) How Three Data Points Become a Complete Profile (39:07) Molly Russell and the Consequences of Algorithmic Profiling (53:55) The Full Proton Ecosystem: Mail, VPN, Drive, Lumo, and Workspace

What if the country that trains the world's engineers finally built the infrastructure to match its talent? In this episode of Eye on AI, Craig Smith sits down with Amith Singhee, Director of IBM Research India and CTO of IBM India and South Asia, to explore where India actually stands in the global AI race and what it will take to close the gap. Amith gives an honest, ground-level assessment of why India has been slow to compete. The talent has always been there. But until recently, the investment, the compute infrastructure, and the institutional intent hadn't come together in a sustained, coordinated way. That's changing, and Amith explains exactly what's different now. He walks through IBM Research India's 27-year presence in the country, the research it's doing on foundation models, hybrid cloud AI deployment, agentic systems, and quantum computing. He also explains why building AI from India doesn't just help India. Working with less data, less compute, and more linguistic diversity forces better engineering and makes IBM's models more generalizable for the entire world. We also get deep into the technical frontier. Why catastrophic forgetting is one of the key unsolved problems standing between current AI and anything more capable. How IBM is already shipping continual learning in practice through its COBOL modernization tools, helping enterprises decode decades of legacy code before the engineers who wrote it are gone. And why agentic AI, for all the hype, still has a mountain of unglamorous enterprise engineering left to climb before it becomes truly reliable. Plus, what Amith would tell an 18-year-old engineer in India today about what skills will actually matter in an AI-driven world. Subscribe for more conversations with the people shaping the future of AI and emerging technology.   Stay Updated:  Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Introduction and Amith Singhee's Background  (06:26) Why IBM Set Up Research in India  (11:45) Can India Compete in AI  (15:18) How IBM Collaborates With Indian Universities  (19:25) Why India Has Been Slow in AI  (24:50) IBM's Hybrid Cloud AI Research Focus  (27:34) How Data Scarcity in India Makes Better AI  (31:18) Fine-Tuning Models Without Losing General Knowledge  (35:03) Continual Learning and Catastrophic Forgetting  (38:25) COBOL and Legacy Code Modernization  (42:11) Agentic AI Hype vs Enterprise Reality  (48:09) What Young Engineers Should Study Today   

What does it actually take to prove that AI delivers real value in the industries that keep the world running? In this episode of Eye on AI, Craig Smith sits down with Debdas Sen, CEO of TCG Digital and Joint Managing Director of Lummus Digital, to explore what serious enterprise AI looks like when it is applied to some of the most complex, high-stakes problems on the planet. Problems like compressing years of catalyst research into weeks, predicting refinery failures before they happen, and accelerating drug development timelines that could determine how long a life-saving medicine takes to reach patients. Debdas has spent nearly 30 years in data and AI, living through every hype cycle from the data warehousing era of 1997 to today's agentic revolution. He makes a compelling case that the AI community has one defining job right now: prove the ROI, or risk another AI winter. We also get into what makes TCG Digital's platform mcube™ different. It is not a horizontal tool. It is a domain-first, agentic AI ecosystem built for the kinds of massive, multi-variable problems that horizontal platforms cannot touch. Debdas breaks down how mcube™ bridges legacy enterprise infrastructure with cutting-edge agentic systems, why hybrid modeling beats pure AI in energy and life sciences, and how the platform keeps private enterprise data protected while still drawing on the best of what public LLMs have to offer. Finally, Debdas shares where he sees the industry heading next, a future where agents from different providers can reason together in a neutral space, where inference and reasoning keep improving, and where the companies that go deepest into domain will pull furthest ahead. Subscribe for more conversations with the people building the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on AI on X: https://x.com/EyeOn_AI TCG Digital Website: https://www.tcgdigital.com/ TCG Digital on LinkedIn: https://www.linkedin.com/company/tcgdigital/      (00:00) Introduction and Meet Debdas Sen (01:30) 30 Years in Data and AI: From Data Warehousing to Agentic Systems (03:02) What TCG Digital Actually Does (04:32) Inside mcube™: How the Platform Works (10:06) Domain vs Horizontal: Why Specificity Wins in Enterprise AI (18:29) Catalyst R&D: Collapsing 12 Months of Research Into One (30:38) Predicting Plant Failures Before They Happen (36:51) Solving the Trust and Hallucination Problem in Enterprise AI (44:51) The Six-Layer Architecture of mcube™ (47:05) What Is Genuinely New About Agentic AI (49:22) What Young People Should Study to Work in Serious AI (53:14) Velocity to Value: Why ROI Must Be Tracked From Day One

In this episode, I sat down with my cohost Craig Smith to break down my weekend at a local bodybuilding show and everything it brought up for me. We talked about how insane it is what the human body can achieve at that level—but also how misunderstood it is. A lot of people think you can just take steroids and look like that, and that's just not reality. It takes years of discipline, precision, and a level of commitment most people aren't willing to touch. That led into a bigger realization for me: I don't think I'll ever step on stage again. Not because I can't—but because I fully understand the level of sacrifice required, and I'm clear that it's not a price I'm willing to pay anymore. From there, we dove deep into the concept of sacrifice—what it actually means, how it scales with the size of your goals, and how most people say they want something without being honest about what it's going to cost them. At the end of the day, the conversation really came down to this: if you want something meaningful, it's going to require real trade-offs. And if you're not willing to make those sacrifices, you don't actually want the goal—you just like the idea of it.   Next Level Links: Work With a Nutrition Coach - Schedule A Consultation Nutrition Coaching - www.becomenextlevel.com   Partner Links: Try Thrive Lab Free For One Month - Start Here Order Supplements From Transform - Shop Here Order Supplements From Cured Nutrition - Shop Here Order Supplements From Legion (use code keynutrition for 20% off first order) - Shop Here   Be Featured on the Show: Apply to be a live calller guest on the show - Submit Application Here Submit Q&A Questions to be read live on the show - Submit Here   Free Guides: Eating Out Guide - Get The Guide High-Protein Fast Food Orders - Get the Guide Macro Food Options Guide - Get The Guide Join Us On Patreon - Join Here   Connect with us on Instagram: Host Brad Jensen – @thesoberbodybuilder Co-Host Craig Smith - @greatestdaymindset Next Level Nutrition – @mynextlevelnutrition

Are you overwhelmed… or just under-supported? In this powerful message from Isaiah 40, Craig Smith challenges a common assumption: that our stress comes from everything happening around us. But what if the real issue is what we're standing on? If you've been trying to push through life on your own strength—or placing your trust in people, success, security, or "shiny things" that don't last—this message will help you see why that approach keeps falling apart. You'll discover: Why overwhelm isn't about your circumstances The hidden danger of "shiny things" that promise peace but don't deliver How your focus shapes your faith (and your future) What it looks like to transfer your trust to something that won't fail God doesn't want you stuck in survival mode. He offers a foundation that can actually hold you—no matter what life throws your way.

What if the country that produces the world's top AI talent finally figured out how to keep it? In this episode of Eye on AI, Craig Smith sits down with Professor Mausam, one of India's leading AI researchers, AAAI Fellow, and founding head of the Yardi School of Artificial Intelligence at IIT Delhi, to get an honest and unflinching diagnosis of why India has fallen so far behind the US and China in artificial intelligence and what it will actually take to close that gap. Mausam breaks down the structural story behind India's deficit. A pipeline of world-class students that gets exported abroad the moment it graduates. A professor shortage so severe that IIT Delhi's entire School of AI has hired only five new faculty members in five years. A government AI mission with the right instincts but not enough speed or boldness. And a brain drain made worse by the very thing India is proud of, its English fluency, which makes its talent the easiest in the world to absorb and the hardest to bring back. Mausam walks through the full picture. How China built its research dominance not through students but through aggressively repatriating senior researchers with real salaries, real lab resources, and real authority to build research cultures from scratch. Why the AlexNet moment in 2012 was actually an equalizer that gave China's fledgling ecosystem a surprise advantage over more established Western research groups. How India's JEE coaching culture and IIT bottleneck are symptoms of a scarcity of quality institutions rather than a broken exam. What the government's AI mission is getting right on compute, data, and sectoral focus, and where the critical gaps remain. And why Mausam believes that bringing one hundred top professors back to India would do more for the country's AI future than any single government program or funding initiative. We also get into the harder questions. Whether AI degrees belong at the undergraduate level or should sit on top of a computer science foundation. Why Mausam no longer holds an optimistic view on AI's impact on software jobs and why he thinks Geoff Hinton's point about plumbers has merit. And what it would actually take for a democracy of 1.4 billion people to stop training the world's AI leaders and start keeping them. Subscribe for more conversations with the researchers, builders, and policymakers shaping the future of artificial intelligence. Stay Updated:  Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Introduction: India's AI Gap and Professor Mausam's Background (02:30) Building the Yardi School of AI at IIT Delhi (07:44) How Far China Has Pulled Ahead in AI Research (12:55) Why India Could Not Follow China's Playbook (29:18) The JEE System, Coaching Culture, and the IIT Bottleneck (30:37) AI Degrees, Job Market Realities, and the Future of Work (44:18) The Real Problem Is Professors, Not Students (48:07) Big Tech Labs in India: Helpful but Not at Scale (51:46) The Government AI Mission: Progress and Gaps (55:20) The Compute and Data Infrastructure Problem (59:54) Can India Close the Gap Before It Is Too Late 

Why IBM Is Betting Everything on Small AI Models In this episode of Eye on AI, Craig Smith sits down with Sriram Raghavan, Vice President of AI at IBM Research, to explore one of the most important debates in enterprise AI right now. Do you actually need a massive model to get world class results? IBM's answer is no, and Sriram breaks down exactly why. Sriram explains why IBM chose to train its Granite models directly using reinforcement learning rather than distilling from larger models like most of the industry. The reason goes beyond performance. It comes down to data lineage, safety alignment, and a belief that small, efficient models are the only sustainable path for enterprises running AI across hybrid cloud environments. We get into the full technical stack behind that bet. How data quality has replaced model size as the real competitive advantage. Why parameter count is becoming the wrong metric entirely. How IBM's inference time scaling techniques allow an 8 billion parameter model to match the performance of GPT-4o and Claude 3.5 on code and math benchmarks. And why IBM is pioneering a new concept called Generative Computing, which treats AI models not as prompt receivers but as programmable computing elements with runtimes, modular LoRA adapters, and proper programming abstractions. Sriram also shares where IBM Research is headed next, including breakthroughs in continuous learning, agent orchestration, and making unstructured enterprise data actually usable at scale.   Subscribe for more conversations with the people building the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Why IBM Skips Distillation and Trains Small Models Directly  (04:50) Did We Even Need Giant AI Models in the First Place? (08:12) How Data Quality Became the New Competitive Moat (11:54) Why Parameter Count Is the Wrong Way to Measure a Model (15:36) Reinforcement Learning Without Losing Broad Capabilities (22:05) Inference Time Scaling: Getting Big Model Results From Small Models (28:12) Generative Computing: Treating AI as a Programming Element (36:40) Why IBM Open Sources and How Small Models Make It Sustainable (41:25) The Path to Continuous Learning Without Rewriting Weights (51:00) IBM's Full Roadmap: Models, Data, and Agents

What if the country that trained the world's engineers finally decided to keep them? In this episode of Eye on AI, Craig Smith sits down with Abhishek, the civil servant leading India's $1.2 billion national AI Mission, to explore how one of the world's largest and most diverse nations is mounting a serious challenge to US and Chinese dominance in artificial intelligence. Abhishek breaks down the honest story behind India's late start. World-class talent, but no research ecosystem to retain it. Digitization without AI-usable data. Compute so scarce that the entire country had fewer than 500 GPUs just two years ago. And a brain drain so severe that the engineers India trained are now running the biggest tech companies in the world, just not from India. Abhishek walks through exactly how the mission is tackling each of those gaps. A subsidized compute program that gives researchers and startups access to 38,000 GPUs at under a dollar per hour. AI Kosh, a national data platform pulling public and private sector datasets into a single AI-ready repository. Centers of Excellence connecting IITs around domain-specific research in agriculture, healthcare, education and mobility. And a sovereign LLM program, with four models already in development and eight more on the way, built specifically for India's languages, voices and needs. We also get into the geopolitics. Where India stands as the US and China carve out competing AI spheres of influence. Why Abhishek is pushing for a UN-led governance framework rather than aligning with either bloc. And what it would actually take for a country of 1.4 billion people to not just catch up, but leapfrog.   Subscribe for more conversations with the people shaping the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Introduction and Abhishek's Background  (02:43) What the India AI Mission Is and How It Started  (04:53) The $1.2 Billion Budget and Total AI Investment in India  (06:36) Data Center Build-Out and the Road to 7 Gigawatts  (08:11) AI Kosh: India's National Data Platform  (10:50) Subsidized GPUs and How Researchers Access Compute  (12:41) Brain Drain, Reverse Migration and Retaining Top Talent  (17:24) Centers of Excellence Across IITs and Key Sectors  (19:21) Expanding Fellowships and Training the Next Generation  (20:11) Why India Started Late and What Changed  (21:48) Sovereign LLMs Built for Indian Languages and Needs  (22:42) The Diversity Challenge and Culturally Relevant AI  (23:16) Government Funding for Foundation Model Development  (24:12) The AI Impact Summit and India's Role on the Global Stage  (24:52) India, China, the US and the Battle for AI Governance  (29:37) The UN Framework and India's Third Way  (31:16) India-China Relations and New AI Partnerships  (32:01) How the $1.2 Billion Budget Was Decided  (33:31) Can India Actually Catch Up With the US and China

In this week's episode, Craig breaks down potential additions to the Chargers current edge room in this year's draft class. Learn more about your ad choices. Visit megaphone.fm/adchoices

Most enterprises are excited about agentic AI. But very few are actually deploying it in production. In this episode of Eye on AI, Craig Smith sits down with Adi Kuruganti, Chief AI and Development Officer at Automation Anywhere, to break down why agentic AI is so hard to get right in the enterprise and what it actually takes to move from a promising pilot to a mission-critical deployment. Adi explains why the future of enterprise automation is not agentic AI alone, but the combination of deterministic and agentic systems working together, and why companies that treat AI as a technology problem instead of a business outcomes problem are setting themselves up to fail. They dig into how Automation Anywhere is orchestrating agents across legacy systems, healthcare platforms, and financial services workflows, why governance and compliance are the first questions every enterprise asks, and how their Process Reasoning Engine is continuously improving agent performance using metadata from over 400 million running processes. The conversation also covers the real timeline to a fully autonomous enterprise, why the POC to production gap is the biggest failure point in enterprise AI today, and what companies that wait too long risk losing to competitors who started the journey earlier. If you want to understand where enterprise AI actually stands today and what it takes to deploy it responsibly at scale, this episode gives you a clear and grounded perspective. Subscribe for more conversations with the people building the future of AI and emerging technology.     Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI     (00:00) Why Enterprises Are Struggling With Agentic AI (02:39) What Automation Anywhere Does and the APA Category Explained (08:01) Deterministic vs Agentic AI: Why You Need Both (10:59) How Human in the Loop Works in Enterprise AI (17:16) The Mozart Orchestrator and Process Reasoning Engine (23:50) How AI Is Upgrading and Replacing Classic RPA (27:31) How Automation Anywhere Works With Enterprise Customers (31:53) The Biggest Challenges of Scaling Agentic AI (41:10) The OpenAI Partnership and What It Means (47:06) Training Staff and Building AI Literacy at Scale (51:39) Staying Close to Customers as the Technology Shifts (53:17) Is the Autonomous Enterprise Actually Coming

You're not the only one feeling overwhelmed. In fact, most of us are carrying more than we were ever designed to handle—and it's starting to show. In this episode of Continuing the Conversation, we go deeper into Isaiah 40 and unpack one powerful truth: God wants to help you overcome what has you overwhelmed. But here's the twist—it might not start with your circumstances. It might start with your orientation. We talk about: Why overwhelm is so common right now (and why it makes sense) The difference between God changing your situation and strengthening you in it How your focus, habits, and inputs shape your anxiety The practical first step that leads to real change This is a real conversation about real life—no pressure, no perfect answers. Just honest steps forward.

What happens when AI writes code faster than anyone can test it? In this episode of Eye on AI, Craig Smith sits down with Dan Faulkner, CEO of SmartBear, to explore one of the most underappreciated risks of the AI coding boom. As tools like Claude Code and Codex push software development to unprecedented speed, the systems built to validate that software are being left behind. Dan makes a distinction that every engineering leader needs to hear: clean code passing unit tests is not the same as an application that actually works. Dan introduces the concept of application integrity, continuous and measurable assurance that your software does everything it was intended to do and nothing it was not. He explains why the gap between what AI builds and what teams actually validate is already creating hidden risk in production, and why that risk compounds the faster you ship. We also get into the new failure modes that agentic AI is introducing. Slop squatting, instruction inversion, cascading errors. These are not theoretical. They are happening now, at scale, in codebases that no human has fully read. Dan also walks through SmartBear's autonomy ladder framework and their newest product BearQ, a team of AI agents that explores your application, builds a knowledge graph, authors tests, runs them, and updates everything as your app evolves. The key distinction: it is built to augment human teams, not replace them. Finally, Dan shares his honest take on the future of software engineering. The fallacy was always that coding was the hard part. The hard part is knowing what to build. That skill is not going anywhere. Subscribe for more conversations with the people shaping the future of AI and emerging technology.   Stay Updated: Craig Smith on X: https://x.com/craigss  Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Introduction and Dan Faulkner's Background  (01:05) What SmartBear Does: Testing and API Lifecycle Management  (03:27) AI Is Outpacing Application Testing  (07:51) Slop Squatting, Instruction Inversion and New AI Failure Modes  (17:31) Black Boxes, Technical Debt and the Expertise Crisis  (22:00) How to Avoid Self-Validating AI Systems  (24:11) The Autonomy Ladder and BearQ  (31:30) Why Testing Must Be Continuous and Everywhere  (36:31) Infrastructure Risk and Automation Bias  (44:11) The Future of QA and New Specialist Roles  (50:44) How Teams Use SmartBear Tools Today  (58:57) The Future of Software Engineering and Human Roles

This episode is sponsored by Modulate. Most voice AI focuses on transcription. Velma takes it further by actually understanding conversations, analyzing tone, timing, stress, and intent using its Ensemble Listening Model architecture. Explore the live preview: https://preview.modulate.ai/ What does it actually mean to build a foundation model for robots? In this episode of Eye on AI, Craig Smith sits down with Sergey Levine, co-founder of Physical Intelligence and professor at UC Berkeley, to explore a fundamentally different approach to building robots, one inspired not by programming a single perfect machine, but by training AI on the broadest and most diverse data possible so robots can learn, adapt, and operate in the unpredictable real world. Sergey explains why the secret to general-purpose robots isn't perfecting one single machine, but training on massive, diverse data from all kinds of robots and even humans. The more variety the model sees, the better it gets. Just like ChatGPT learned from all the text on the internet, robotic foundation models learn from every robot that has ever moved, grabbed, or interacted with the real world. We also get into the big humanoid robot debate. Are they the future, or is it mostly hype? Sergey gives an honest and technical take on why the form factor conversation is changing now that foundation models exist, and why that actually opens the door for more creativity, not less. Finally, Sergey shares what he's most excited about next, building a true data flywheel where robots get smarter the more they are deployed, creating a continuous learning cycle that could change everything. Subscribe for more conversations with the people building the future of AI and emerging technology. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI   (00:00) Introduction: What Are Foundation Models for Robots? (01:44) Meet Sergey Levine: Physical Intelligence and UC Berkeley (02:51) Breaking Down Foundation Models for Non-Technical People (06:46) Why Real World Data Beats Simulation (15:00) Building a Broad Robotics Foundation From Scratch (24:00) The Open World Problem in Robotics (40:00) Generalist vs Specialist Robots: Which Wins? (47:00) Humanoid Robots: Real Innovation or Just Hype? (55:10) The Future: Continuous Learning and the Data Flywheel (56:23) Guilty Pleasure: Sci Fi and Thinking Beyond the Limits

Easter is the most important moment in history… So why do so many of us miss what it really means? In this powerful Easter message from John 13, Craig Smith walks through a moment most people overlook—when Jesus asked His disciples a simple but life-changing question: "Do you understand what I have done for you?" Before the cross. Before the resurrection. Jesus gave them a picture of everything He was about to do—and why. In this message, you'll discover: Why the cross was never an accident—it was always the plan What Jesus' actions reveal about His love for you The difference between religion and the gospel Why pride keeps us from receiving what Jesus already did This message is honest, direct, and deeply personal. Because the question isn't just for them—it's for you.

AI has been trained like software. But what if it should be grown like life? In this episode of Eye on AI, Craig Smith sits down with Sebastian Risi, professor and leading researcher in neuroevolution and artificial life, to explore a fundamentally different approach to building intelligence, one inspired by how nature evolves, grows, and adapts. Sebastian explains why traditional AI systems are limited by fixed architectures and one-time training, and how evolutionary algorithms can create systems that continuously learn, self-organize, and even grow their own neural structures over time. They dive into concepts like plastic neural networks that keep updating during their lifetime, AI systems that can recover from damage, and models that develop from a single "cell" into complex structures, similar to biological organisms. The conversation also explores how combining large language models with evolutionary search could unlock more creative and open-ended problem solving, from merging specialized models to building AI systems capable of generating and testing scientific ideas. If you want to understand where AI is headed beyond today's transformer models, and why the future may look more like living systems than software, this episode offers a clear and thought-provoking perspective. Subscribe for more conversations with the people building the future of AI and emerging technology. Stay Updated: Craig Smith on X: https://x.com/craigss Eye on A.I. on X: https://x.com/EyeOn_AI (00:00) Why copy nature's evolution for AI (01:20) What neuroevolution actually means (05:52) How evolutionary search replaces gradients (08:03) Plastic neural networks and continuous learning (11:53) Growing neural networks like living systems (18:08) Scaling challenges and limits of growth (23:16) Can evolving systems replace LLM training (27:28) Continual learning and model merging (30:27) Artificial life, self-repair, and resilience (35:10) AI scientists and evolution with LLMs

In the return episode of IG5OI Craig takes a look at prospects that fit the profile the Chargers may be targeting at wide receiver in the upcoming NFL draft. Learn more about your ad choices. Visit megaphone.fm/adchoices

Ever feel like you're stuck in the middle? Not where you used to be… Not where you want to go… Just somewhere messy, uncertain, and honestly a little scary. In this message from Mark 4, Jesus asks a question that cuts straight through the noise: "Why are you so afraid?" It's not just about fear. It's about trust. In this week's message, Craig talks about: Why the "middle" of life feels so hard—and why God often does His best work there The difference between following Jesus casually and actually committing to Him What fear reveals about what we believe about God How to move forward when you feel stuck, overwhelmed, or unsure If you've been anxious, stuck, or questioning whether God really cares… this message is for you.

On today's episode of The Brad Jensen Show, Craig Smith and I dive into the sayings we cannot stand in the health, fitness, and personal development space. You know the ones. The phrases that sound harmless on the surface but actually keep people stuck, playing small, and buying into their own excuses. We break down the victim mindsets, the self-sabotaging statements, and the subtle language patterns that quietly wreck progress without people even realizing it. Between my 15 years in the health and fitness space and Craig's 20 years of clinical experience, we've heard it all and today we call it out. This one is equal parts informative and funny, but also direct as hell. If you've ever caught yourself saying things like "I just can't," "this is just how I am," or "I'll start when life slows down"… this episode might hit a little close to home. And that's the point. Because once you become aware of the language that's holding you back, you can finally start changing it and changing your life along with it.   Next Level Links: Work With a Nutrition Coach - Schedule A Consultation Nutrition Coaching - www.becomenextlevel.com   Partner Links: Try Thrive Lab Free For One Month - Start Here Order Supplements From Transform - Shop Here Order Supplements From Cured Nutrition - Shop Here Order Supplements From Legion (use code keynutrition for 20% off first order) - Shop Here   Be Featured on the Show: Apply to be a live calller guest on the show - Submit Application Here Submit Q&A Questions to be read live on the show - Submit Here   Free Guides: Eating Out Guide - Get The Guide High-Protein Fast Food Orders - Get the Guide Macro Food Options Guide - Get The Guide Join Us On Patreon - Join Here   Connect with us on Instagram: Host Brad Jensen – @thesoberbodybuilder Co-Host Craig Smith - @greatestdaymindset Next Level Nutrition – @mynextlevelnutrition

In this episode of The Brad Jensen Show, I'm joined by my regular cohost Craig Smith and we dive into a pattern we see all the time with high performers. A lot of people are crushing it in business, leadership, or other areas of life… but their health, relationships, or personal life are falling behind. Craig and I break down some of the biggest reasons this happens. From getting completely lopsided into one area of life to neglecting the habits that actually keep everything running well long term. Between my experience coaching thousands of clients and Craig's background as a therapist, we unpack why high achievers often struggle to transfer the same discipline and focus they have in business into their health and other meaningful goals. If you feel like you're winning in some areas of life but other important areas keep slipping through the cracks, this episode will help you understand why and what to do about it. Topics we cover: Why high performers often struggle with their health The problem with living a "lopsided life" Why success in business doesn't automatically translate to health The identity shifts required to level up all areas of life How to start creating balance without losing your edge   Register for our Masterclass on March 23, 2026 - Register Here   Next Level Links: Nutrition Coaching Free Consultations - Schedule Here Nutrition Coaching - www.becomenextlevel.com   Partner Links: Try Thrive Lab Free For One Month - Start Here Order Supplements From Transform - Shop Here Order Supplements From Cured Nutrition - Shop Here Order Supplements From Legion (use code keynutrition for 20% off first order) - Shop Here   Be Featured on the Show: Apply to be a live calller guest on the show - Submit Application Here Submit Q&A Questions to be read live on the show - Submit Here   Free Guides: Eating Out Guide - Get The Guide High-Protein Fast Food Orders - Get the Guide Macro Food Options Guide - Get The Guide Join Us On Patreon - Join Here   Connect with us on Instagram: Host Brad Jensen – @thesoberbodybuilder Co-Host Craig Smith - @greatestdaymindset Next Level Nutrition – @mynextlevelnutrition