Advertise on podcast: Digital Disruption with Geoff Nielson

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionnow. Tech moves fast. So does work. Digital Disruption NOW helps you keep up and make sense of what matters. All signal. No static. An Infotech production. Are AI data centers in space a practical solution for the future or just an expensive fantasy? We analyze the technical reality. This week we’re covering the AI market rout, datacenters in space, and the Binance hack. In this episode: 0:00 The AI Rocket Ambition 1:08 Big Tech’s AI Spending Hangover 4:04 The Looming AI Cost Reckoning 5:56 Managing AI Token Costs 9:54 Is Frontier AI Overkill? 11:12 Who Pays for AI Behind the Scenes? 13:12 Will Efficiency Gains Bring AI Costs Down? 15:05 Infotech CIO Analytics 16:18 Project Sun Catcher: Data Centers in Orbit 20:43 Cooling, Repairs, and the Challenges of Space Computing 25:05 What Would Make Space Data Centers Viable? 26:29 Who Owns Your Data in Space? 27:32 The Binance Heist and Crypto Security 31:13 Zero Trust, Permissions, and Security Failures 33:04 Can Crypto Exchanges Be Trusted? 37:29 Lessons from the Crypto Hack 40:03 Wrap-Up and What’s Next Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG Check out other episodes from the Digital Disruption podcast: https://youtube.com/playlist?list=PLIImliNP0zfxRA1X67AhPDJmlYWcFfhDT&feature=shared

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organic As AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruption What if we can never fully predict or understand AI and need to rethink how we use it? Stephen Wolfram, creator of Mathematica and Wolfram|Alpha, explains why artificial intelligence remains fundamentally unpredictable and how we can make it useful despite those limits. Stephen joins us to discuss large language models, AI-generated code, and the difference between generating convincing answers and performing precise computation. He explains how combining generative AI with computational tools can help bridge that gap and why understanding what you’re building matters more as automation advances. The conversation also explores how AI could transform cybersecurity, powering both attacks and defenses. Stephen considers how these increasingly complex interactions could outpace human understanding and what that means for oversight and AI transparency. He explains why safeguards need to operate outside the AI itself to limit the consequences of unpredictable behavior. Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 AI beyond human understanding 01:29 AI hype vs. long-term potential 05:35 ChatGPT and natural language interfaces 06:47 Combining generative AI with Wolfram Language 08:41 CIO Analytics: API-Driven Advisory 10:00 Understanding the world through computation 13:17 How Simple rules create complex behavior 16:15 Human-like AI vs. precise computation 21:08 Why AI struggles with 100% accuracy 22:39 McLean & Company’s Human-Centric AI program 23:37 Where AI works and where it falls short 27:17 The risks of AI-generated code 29:49 Why understanding matters more than implementation 33:51 Can we understand AI’s black box? 36:37 Computational irreducibility explained 39:49 Why AI needs external guardrails 42:08 The limits of AI control 43:25 AI-powered cyberattacks and defenses 45:03 Automation and the future of work 49:48 How Wolfram research uses automation 54:00 AI coding and the rise of small software tools 55:57 Choosing what to build when more is possible 59:58 Finding value as an AI startup 01:01:33 Leading innovation at Wolfram research 01:07:47 Bringing Wolfram|Alpha to life 01:10:48 Why managing scientific research is different 01:13:01 Building teams that think broadly 01:15:07 Matching people to projects and preserving their work 01:19:30 Advice for founders: Build something you want 01:21:03 Why CEOs need to understand their business 01:24:03 Hiring beyond the polished interview 01:26:15 Final thoughts 01:27:02 About Infotech Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionnow. Tech moves fast. So does work. Digital Disruption NOW helps you keep up and make sense of what matters. Coming to you from the Masonic Temple, Digital Disruption NOW is the latest podcast in the Digital Disruption network, bringing you a weekly take on tech, work, and what it all means. We break down the biggest headlines, debate the hottest topics, and explore how technology is changing the way we live and work. From the news everyone’s talking about to the developments you might have missed, get real perspectives and insights you can actually use. All signal. No static. An Infotech production. Is AI delivering real business value, or just bigger promises? Geoff and Jeremy break down Anthropic’s IPO prospectus, debate AI productivity and ROI beyond Big Tech, and examine OpenAI’s claims about modernizing legacy COBOL systems. From Claude’s growth and AI bubble risks to the gap between faster tasks and measurable business results, explore what the headlines mean for tech and work. In this episode: 00:00 Intro: AI, productivity, and the guacamole problem 00:28 Welcome to Digital Disruption NOW 00:59 Anthropic’s IPO prospectus: promises and risks 03:58 Anthropic’s finances: revenue, losses, and profitability 06:28 Can Claude justify Anthropic’s valuation? 11:48 AI bubble risks and an interconnected tech economy 17:12 Anthropic IPO: final takeaways 18:08 CIO Analytics: a single platform to run IT 19:16 Apollo’s AI payoff report: Big Tech vs. everyone else 20:46 The AI productivity paradox 23:23 Is AI investment being measured in the right companies? 26:41 Will more AI actually improve productivity? 29:08 Why individual time savings don’t guarantee business growth 33:20 Is AI becoming essential to staying competitive? 34:52 Can OpenAI solve the COBOL code crisis? 36:59 Why rewriting code isn’t the same as replacing systems 38:03 The reality of legacy mainframe migration 40:35 The doorman fallacy: what automation overlooks 42:09 Why institutional knowledge still matters 43:23 Episode recap and closing credits Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG Check out other episodes from the Digital Disruption podcast: https://youtube.com/playlist?list=PLIImliNP0zfxRA1X67AhPDJmlYWcFfhDT&feature=shared

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organic As AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruption AI promises to transform the economy. When will that promise translate into measurable business growth? Entrepreneur and Silicon Valley Girl creator Marina Mogilko explores the gap between AI hype and economic impact, sharing where she sees opportunities for businesses, workers, and entrepreneurs. Marina joins us to discuss AI productivity, entrepreneurship, and the future of work. She examines why AI’s economic contribution remains difficult to measure, even as it helps small teams do more and creates new revenue opportunities. Drawing on her own experience, Marina explains how AI could lower the barriers to starting a business for solopreneurs and women entrepreneurs. She also questions the idea of a one-person billion-dollar company. From organizing company data to building targeted AI agents, the conversation explores what it takes to turn AI adoption into business value. Marina shares why experience, strategic thinking, and accountability remain essential, and how leaders can prepare their teams for sustainable growth. Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 01:04 Why AI’s economic impact is hard to measure 04:16 The case for optimism about AI 05:49 How AI is changing tasks and productivity 09:24 CIO Analytics: API-Driven IT Advisory 10:15 Turning AI productivity into new revenue 13:16 Lowering the barriers to entrepreneurship 14:43 Can one person build a billion-dollar company? 17:18 The AI agents marina uses in work and life 20:19 Which tasks are worth automating? 23:32 Why better AI results start with organized data 28:28 How AI can reinforce bad business decisions 30:53 Using AI as a data analyst while keeping human judgment 32:01 Building an authentic brand without chasing AI doom 37:44 Making AI useful and accessible to more people 40:23 Women, AI adoption, and the need for relatable use cases 46:49 Why education still matters in the AI era 49:29 Questioning AI predictions and taking responsibility 53:10 Lessons on entrepreneurship and long-term success 55:55 Avoiding burnout and knowing when to pivot 59:20 Finding the confidence to change careers 1:00:52 Why telling your team to “Use AI” isn’t enough 1:02:50 Building entrepreneurial teams and managing AI agents 1:04:55 Lead AI adoption from the front 1:05:36 McLean & Company’s Human-Centric AI Program Connect with Marina: LinkedIn: https://www.linkedin.com/in/marinamogilko/ Instagram: https://www.instagram.com/siliconvalleygirl/ X: https://x.com/siliconvalleymm Facebook: https://www.facebook.com/marina.mogilko Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

If AI can free up half a company’s labor capacity, what happens to the people doing the work? Ravin Jesuthasan describes AI transformations that have freed up 40–50% of labor capacity. Is your organization ready for what that means for its workforce? The futurist and bestselling author explains how AI is reshaping the future of work and why its productivity gains don’t have to translate into layoffs. Ravin joins Geoff on this episode of Digital Disruption to discuss generative AI, AI agents, and the impact of automation on jobs. He explains why entry-level roles are under pressure, how traditional career paths are changing, and why judgment, empathy, and curiosity are becoming increasingly valuable. Drawing on examples from Standard Chartered and Unilever, he explores how organizations can prepare employees for new opportunities through upskilling and reskilling. He breaks down what it means to build a skills-powered organization where learning becomes part of everyday work. Ravin also shares how leaders can reinvest AI productivity gains in employee wellbeing, better customer experiences, and continued innovation. Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 00:40 AI frees up half the work. what happens next? 01:12 How AI is reshaping the future of work 03:30 How AI changes the cost of work and access to talent 06:23 Will AI replace all human work? 09:40 Is the fear of becoming obsolete justified? 12:12 McLean & Company’s human-centric AI program 12:52 AI and the erosion of the entry-level career ladder 17:32 What does “work ready” mean in the age of AI? 19:51 Why human judgment is becoming an essential skill 20:58 How to build a skills-powered organization 23:20 Making learning part of everyday work 24:38 Reskilling employees for new career opportunities 26:23 Turning workforce transformation into action 29:56 Setting a vision and proving ROI with focused pilots 32:15 Who should own workforce transformation? 33:35 Involving employees and preparing them for what comes next 35:12 Unilever’s approach to reskilling and career transitions 36:43 Why digital transformations fail 39:17 Moving from one-time transformation to continuous reinvention 41:16 Making space for learning and employee wellbeing 42:34 How to reinvest AI’s productivity gains 45:44 Why IT, HR, and business leaders need to work together 48:15 Why adding AI isn’t enough to transform work 51:12 The value of outside perspectives in AI transformation 53:13 Final Advice: Learn, unlearn, and relearn 54:40 About Infotech Connect with Ravin: LinkedIn: https://www.linkedin.com/in/ravinjesuthasan/ X: https://x.com/RavinJesuthasan Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Is AI consciousness already here and can we reclaim our technological optimism? Google’s Blaise Agüera y Arcas shares why he believes AGI has already arrived and what AI can teach us about consciousness, cooperation, and the human mind. Blaise joins us on this episode of Digital Disruption to talk about AI consciousness, large language models, and why intelligence is inherently social. He explains how AI agent swarms work together, what recursive self-improvement looks like today, and why he questions the idea that smarter machines will inevitably dominate humanity. He questions why we find it easier to imagine catastrophe than a better future. And this conversation examines how negative news shapes our expectations of AI, and why taking its risks seriously can coexist with optimism about its potential. From AI alignment and mass surveillance to jobs and economic inequality, Blaise considers whether our institutions are ready for the changes ahead. He shares how AI could accelerate progress in medicine, robotics, and climate solutions, while emphasizing the work needed to turn those possibilities into reality. This episode asks an important question: As AI becomes more capable, how do we make sure the benefits reach everyone? Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 02:12 Rethinking artificial intelligence 04:35 Can technology be considered alive? 06:13 What does it mean for AI to be conscious? 08:23 Multi-agent systems and the role of self-awareness 11:48 Could AI have a subjective experience? 17:49 What split-brain experiments reveal about consciousness 20:49 Building your AI strategy with Infotech 21:56 The Self: One mind or many parts? 23:38 How LLMs differ from human minds 28:19 Octopus intelligence, AI agent swarms, and identity 32:52 Why Human Intelligence Is Collective 38:19 Why Blaise believes AGI is already here 43:59 Multi-agent AI and the next frontier of intelligence 47:25 Recursive self-improvement and the singularity 50:41 AI coding agents and the risks of faster automation 54:18 AI Alignment: whose values should AI follow? 58:20 Will smarter AI dominate humanity? 1:01:42 Mass surveillance, power, and human disempowerment 1:04:09 AI breakthroughs in medicine, robotics, and space 1:08:12 Why are we so pessimistic about the future? 1:11:29 Why AI doom gets more clicks 1:13:16 Taking AI researchers’ fears seriously 1:16:42 Nostalgia and the accelerating pace of change 1:21:08 Is our economy ready for AI? 1:24:07 AI, job loss, and the fear of losing income 1:26:36 What should leaders and society do next? 1:29:23 AI, climate change, and clean energy 1:31:06 Moving AI computing into space 1:31:42 Final thoughts 1:32:06 About Infotech Connect with Blaise: LinkedIn: https://www.linkedin.com/in/blaise-ag%C3%BCera-y-arcas-85626a42/ X: https://x.com/blaiseaguera IG: https://www.instagram.com/blaiseaguera Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Predictive AI often gets ignored, yet it may hold the real key to business value in the current tech landscape. Machine learning expert Eric Siegel, author of The AI Playbook and Predictive Analytics, joins the Digital Disruption podcast to explain why organizations should invest at least as much in predictive AI as they do in generative AI. He breaks down how predictive AI can improve real-world operations, why so many AI pilots fail to reach deployment, and where the promise of autonomous AI agents encounters reliability challenges. While generative AI captures the headlines, Eric argues that more dependable returns often come from systems that predict outcomes and improve decision-making. The conversation explores the differences between predictive and generative AI, why meaningful business value comes from deployment rather than impressive demos, and the limitations of fully autonomous AI agents and artificial general intelligence. Tune in to learn how predictive AI could make generative AI more reliable, why business leaders and data scientists need to work together, and whether AI will really cause a job apocalypse. Like and follow for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why businesses may be investing in the wrong AI 00:47 Predictive AI vs. generative AI 03:01 How large language models fit into predictive AI 06:59 What kind of AI is solving real-world problems? 08:06 The two “wows” of AI: Impressive demos vs. deployment 09:28 Build your AI strategy with Info-Tech 10:37 Why predictive AI is still delivering business value 12:32 Why most AI pilots fail to reach production 16:25 AI hype and mismanaged expectations 19:31 AI agents, AGI, and the promise of autonomy 20:44 Can predictive AI make generative AI more reliable? 23:57 Why full AI autonomy remains unrealistic 26:59 Large language models vs. human intelligence 29:21 The limits and diminishing returns of AI models 31:35 What businesses are getting wrong about AI 35:35 Bridging the gap between technology and business leaders 37:18 Why leaders need a semi-technical understanding of AI 38:59 Three questions every predictive AI project must answer 42:22 Will AI replace developers and other technical roles? 49:29 Who should own AI strategy and accountability? 53:41 Is AI creating the productivity gains we were promised? 55:49 Could future technology overcome today’s AI limitations? 59:21 How organizations can unlock more value from AI 1:01:43 Eric Siegel’s six-step AI deployment framework 1:04:42 Why AI is a business improvement project, not a tech install 1:06:02 What’s new in The AI Playbook 1:09:30 Eric’s advice for business and technology leaders 1:10:46 About Info-Tech Connect with Eric: LinkedIn: https://www.linkedin.com/in/predictiveanalytics/ X: https://x.com/predictanalytic?lang=en IG: https://www.instagram.com/eric_siegel/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

The robot workforce is already here. AI-powered humanoid robots are entering factories and warehouses to address a growing labor gap, but are they filling jobs or replacing the people who do them? Peggy Johnson, CEO of Agility Robotics, joins us to talk about how Digit is moving from robotics demonstrations into real workplaces. She explains why humanoid robots could become essential to manufacturing and logistics, how AI is accelerating their capabilities, and why safety remains the biggest barrier to widespread adoption. From physical AI and labor shortages to robot fleet managers and the future of work, this episode looks beyond the fear of robot overlords to ask: how will humans and robots work together in the years ahead? Subscribe for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why humanoid robots may be essential 00:47 Peggy Johnson, CEO of Agility Robotics 01:41 Are humanoid robots creating a dystopian future? 03:43 How workers respond to robots in the workplace 05:42 Why build robots in the human form? 07:27 Will humanoid robots replace human jobs? 11:45 Why reshoring manufacturing will require robotics 14:12 Info-Tech AI strategy 14:42 What humanoid robots could do by 2032 17:35 The biggest barrier to adoption: Robot safety 19:17 Why robots in the home are still years away 22:13 How big and powerful is agility robotics’ Digit? 24:44 Can humanoid robot accidents be prevented? 28:29 Competing with Elon Musk and Tesla Optimus 30:56 What separates deployment from a robotics demo 33:37 How companies deploy humanoid robots 37:01 Which industries are adopting robotics? 39:24 Scaling production to meet demand 41:08 How AI is accelerating humanoid robotics 45:36 How digit makes decisions on the factory floor 48:52 Hardware and software upgrades for robots 50:57 What comes after agility robotics’ Digit? 53:22 Will robots eventually do everything humans can? 55:58 The future of physical AI and automation 58:13 Peggy Johnson’s advice for business and tech leaders 59:32 About Info-Tech Connect with Peggy: LinkedIn: https://www.linkedin.com/in/peggyljohnson/ X: https://x.com/agilityrobotics IG: https://www.instagram.com/agility_robotics/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What is PDoom, and why are the people building artificial intelligence willing to risk human extinction? Kevin Roose, a New York Times technology columnist, Hard Fork co-host, and author of The AGI Chronicles, shares what he learned from interviewing more than 150 people inside the world’s leading AI companies. Kevin joins us on Digital Disruption to talk about what artificial general intelligence really means and how fear, ego, rivalry, and mistrust are accelerating the race between OpenAI, Anthropic, and Google DeepMind. He also explains why AI leaders compare this moment to the Manhattan Project: if they don’t build AGI first, someone more dangerous might. Kevin also shares why he estimates a 10% chance of AI-caused extinction and discusses the private fears of AI researchers, government regulation, autonomous AI agents, and whether the AI boom is a bubble or the beginning of a profound transformation. This episode moves beyond the hype to ask an important question: If advanced AI is inevitable, how much control do we still have over what happens next? Subscribe and follow for more conversations about AI, technology, innovation, and digital transformation. In this episode: 00:00 Why AI builders fear human extinction 00:43 Inside the race to build AGI 01:24 What does AGI actually mean? 05:16 AI safety warnings or marketing hype? 07:27 The rivalries driving the AI race 08:44 Building a boardroom-ready AI strategy 09:51 The personal feuds behind AGI 10:58 AI’s Manhattan Project mindset 12:27 Is AI the new atomic bomb? 14:58 Can advanced AI be contained? 16:28 AI regulation and the global arms race 17:35 What is P(doom)? 19:54 What will force governments to act? 21:29 What AI researchers say in private 23:08 Why the public backlash is growing 26:15 Why Kevin Roose changed his mind about AI 29:42 Is advanced AI inevitable? 32:28 AGI and the point of no return 34:38 The race to automate AI research 36:23 AI and gradual human disempowerment 40:10 What happens when AI masters your skills? 42:18 Will AI liberate us or replace us? 44:18 The AI claims Kevin does not believe 46:21 Is the AI boom a financial bubble? 50:20 AI labs and economic concentration 55:08 Inside the AGI chronicles 57:07 How should people prepare for AI? 58:29 About Info-Tech #ai #futureofwork #technologypodcast #aibubble #bigtech #artificialintelligence #technology #datacenter #agi #anthropic #futureofai Connect with Kevin: LinkedIn: https://www.linkedin.com/in/kevin-roose/ X: https://x.com/kevinroose IG: https://www.instagram.com/kevinroose/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Why have the United States and China pulled so far ahead in the global technology race? Mehran Gul, author of The New Geography of Innovation, argues that the answer goes far beyond individual companies or breakthrough technologies. In this episode, we sit down with Mehran to discuss how successful innovation ecosystems are actually built, why Silicon Valley remains so difficult to replicate, and how China rapidly emerged as a global technology superpower. We also talk about why Europe and India have struggled to produce technology giants at the same scale, and how talent, capital, universities, government, and entrepreneurship shape long-term competitiveness. Mehran also breaks down the extraordinary concentration of money flowing into AI companies like OpenAI, Anthropic, and Nvidia, whether today’s AI valuations are sustainable, and why a major market correction could still happen without ending America’s technological dominance. From AI investment and venture capital to Silicon Valley, China, Europe, India, and the future of global innovation, this episode looks beyond the AI hype to ask a much bigger question: who will actually shape the next era of technology? Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 The AI bubble and America’s technology lead 01:47 The new geography of innovation 05:30 How China became a technology superpower 09:13 Can other countries replicate China’s success? 13:17 What does “innovation” actually mean? 16:21 Are tech valuations measuring real innovation? 21:03 Does geography determine who wins in technology? 25:01 Will the U.S. and China dominate the next decade? 29:31 Why Europe’s push for tech sovereignty is struggling 33:05 Can government policy actually create innovation? 37:24 PayPal vs. Skype: How innovation creates more innovation 39:47 Is America’s technology dominance a zero-sum game? 43:52 Who is the world’s third-largest technology power? 45:07 Why “indispensability” may matter more than tech sovereignty 47:00 What This global tech race means for business leaders 48:32 Why AI investment is becoming more concentrated 51:29 Are we betting too much on a few tech leaders? 53:35 What Japan’s collapse can teach us about U.S. tech 56:13 Could the AI bubble actually burst? 59:22 Could China overtake the U.S. in Technology? 1:03:29 When government helps and hurts innovation 1:05:51 Predictions for the next era of global technology 1:07:50 Do We need to redefine innovation? 1:10:02 Where business leaders should look for innovation 1:14:02 Why venture capital isn’t actually global 1:18:00 Final thoughts 1:19:41 About Info-Tech Research Group Connect with Mehran: LinkedIn: https://www.linkedin.com/in/mehrangul?originalSubdomain=ch X: https://x.com/mehrangul_ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we in an AI bubble? Veteran Silicon Valley investor Bill Reichert says yes, but that doesn’t mean the AI revolution is slowing down. In this episode we sit down with Bill Reichert, General Partner at Pegasus Ventures, to discuss the unprecedented investment pouring into AI, why many AI startups will fail, and where the next wave of innovation could emerge. This conversation highlights everything from data centers and quantum computing to China’s growing technology ecosystem and what businesses need to do to innovate and compete. Bill also shares his “Yellow Jacket Paradox,” raising a bigger question about the future of AI: If biological intelligence can accomplish so much with so little energy, could a fundamentally new AI architecture eventually disrupt today’s LLMs, data centers, and AI leaders? Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 The AI bubble is here 01:02 Why this tech cycle is different 03:30 Is AI growth sustainable? 04:18 Why most AI startups will fail 06:11 What separates AI winners from the hype 09:08 The “unfair advantage” in AI 10:59 Where is the next big AI opportunity? 13:16 Investing beyond generative AI 18:13 Why AI is becoming a commodity 19:05 The data center and energy opportunity 20:17 How AI is transforming every industry 22:23 Is AI changing venture capital? 26:13 Does more investment create better technology? 29:01 China, the US, and the global innovation race 34:28 The race for quantum computing 36:51 Is China really just copying the west? 40:06 Why big companies struggle to innovate 45:54 Startups as corporate innovation labs 47:29 How to spot an overhyped tech vendor 49:13 Why companies need to test before they invest 51:04 Why innovation pilots fail 52:49 Escaping “pilot hell” 54:54 Will the pace of innovation ever slow down? 57:30 How AI changes the future of work 59:48 Does AI mean we’ll have to work harder? 01:03:06 The leadership mistake that causes burnout 01:06:08 Control vs. unlimited growth 01:07:12 The “Yellow Jacket Paradox” 01:09:29 Why today’s AI architecture may be wrong 01:11:13 Will today’s data centers become obsolete? 01:13:38 The price of innovation 01:14:08 Closing thoughts Connect with Bill: LinkedIn: https://www.linkedin.com/in/billreichert/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Hany Farid, one of the world’s leading experts on deepfakes and digital forensics, joins us to explain why AI-generated content is pushing us toward a world where we can no longer trust what we see, hear, or even who we’re talking to online. From AI-generated misinformation and social media manipulation to voice cloning, deepfake video calls, and North Korean IT workers infiltrating major companies, Hany breaks down how rapidly the threat landscape is evolving. He explains why humans are not good at detecting deepfakes, how digital forensics experts actually identify manipulated media, and why organizations need to rethink cybersecurity, remote hiring, and digital identity. This episode also dives into Big Tech’s role in the crisis, whether regulation and liability can make technology safer, the growing influence of large language models on how we access information, and what it will take to rebuild trust online. Despite the risks, Hany remains optimistic about AI’s potential. The challenge, he argues, is learning from the mistakes of the social media era and finding a way to harness AI’s power without sacrificing safety, security, and trust. Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, and digital transformation. In this video: 00:00 North Korean IT workers are already inside companies 00:41 Welcome to a “trust no one” digital world 01:49 How much of the internet is already fake? 04:59 Are we heading toward the dead internet? 07:06 What happens when we can’t agree on facts? 08:20 The existential threat of a post-truth world 09:49 Could AI control the information we see? 11:33 Who is manipulating us online? 13:20 How AI is supercharging scams and fraud 15:41 Why you can’t reliably detect a Deepfake 17:28 Should Big Tech be held liable? 19:37 Hany’s Advice: Get social media off your phone 21:26 Can liability force Big Tech to change? 24:25 Should kids be banned from social media? 25:37 The real problem with social media’s business model 28:08 Will Big Tech control the future of AI? 31:20 “China will beat us” and the case against AI regulation 33:31 How experts actually detect deepfakes 36:16 How real-time face swap deepfakes work 39:39 The Deepfake threat facing businesses 40:25 AI fraud is already costing companies millions 41:47 How fake workers get hired 42:49 Why voice biometrics are no longer secure #ai #futureofwork #technologypodcast #cybersecurity #deepfakes #digitaltrust #bigtech #aivoice #digitaltransformation #futureofjobs #futureofai #tedtalk Connect with Hany: LinkedIn: https://www.linkedin.com/in/hany-farid-40a97935/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Claire Stapleton spent 12 years at Google, going from one of the company's biggest believers to one of its most prominent employee organizers. In this episode, former Google communications leader, Google Walkout organizer, and Don’t Be Evil author Claire Stapleton reveals what happened inside Google as its celebrated culture of openness, employee empowerment, and idealism began to change. She takes us inside Google’s transformation from a company that believed people were at the heart of its success to a Big Tech giant grappling with bureaucracy, employee distrust, workplace activism, and questions about its values. She explains what led thousands of Google employees to walk out in protest, what happened after employees challenged leadership, and why speaking up inside powerful organizations can come with serious consequences. We also talk about AI and the future of work, tech layoffs, corporate culture, employee activism, leadership, workplace ethics, the changing relationship between employers and employees, and why the sweeping promises coming from today’s AI companies remind Stapleton of Google’s early years. As companies once again compete for elite technology talent while promising to change the world, could Silicon Valley be repeating the same cycle? Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, leadership, and digital transformation. In this video: 00:00 Intro 00:10 How Google’s culture changed 01:33 Claire Stapleton’s 12 years at Google 06:14 Inside Google’s early “change the world” culture 10:50 Shift in language 11:28 What happened to Google? 18:42 The events that led to the Google Walkout 25:31 Organizing the historic Google Walkout 28:59 How Google responded to employee activism 35:16 Would Claire organize the Walkout again? 39:19 The danger of tying your identity to your employer 44:29 What should you do when your employer violates your values? 50:35 Did Silicon Valley lose its people-first culture? 51:38 Are today’s AI companies repeating Google’s mistakes? 55:03 Why being people-first is good for business 56:05 What Google’s leadership got wrong 01:00:09 Why women led the resistance inside Google 01:01:48 The role of men and allies in workplace activism 01:05:58 Why women take on more unpaid work 01:08:19 How leaders can build a better workplace culture 01:11:23 Closing thoughts #futurofwork #google #workplaceculture #leadership #bigtech #aiandjobs #siliconvalley #techleadership #techlayoffs #techpodcast Connect with Claire: LinkedIn: https://www.linkedin.com/in/claire-stapleton-868a935 X: https://x.com/clairewaves Facebook: https://www.instagram.com/clairewaves/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Data center economics are coming under increasing scrutiny. Learn why power constraints could signal a major market correction and why the future of artificial intelligence may depend less on software and more on power grids, data centers, semiconductor chips, and the physical infrastructure powering AI. In this episode, TDK Ventures Investment Director Ankur Saxena joins Geoff Nielson to talk about the economics driving today's AI race. From Nvidia GPUs and hyperscaler spending to semiconductor shortages, AI infrastructure, robotics, edge AI, and quantum computing, Ankur explains why the biggest challenges facing AI aren't just technical, they're economic, physical, and increasingly difficult to ignore. This conversation examines whether today's AI investment boom is sustainable, what could trigger the next wave of market corrections, and where the greatest opportunities lie for investors, startups, and technology leaders. If you're wondering where AI is really headed and what it means for business leaders, investors, CIOs, and the future of technology, this episode is for you. In this episode: 00:00 Intro 00:20 AI's biggest problem isn't software, it's infrastructure 01:37 Ankur Saxena on the future of AI & why he's optimistic 03:20 Is the AI investment boom becoming a bubble? 07:40 AI prototyping for enterprise leaders 08:50 The AI Gold Rush: Are investors chasing hype? 10:17 Why AI infrastructure economics matter more than ever 12:09 The hidden bottleneck: Power, data centers & AI growth 15:45 AI data centers explained 19:53 Supply, demand & what happens when AI gets expensive 21:03 Why AI demand isn't slowing down anytime soon 26:33 Should every enterprise care about AI infrastructure? 27:15 Why most companies aren't ready for AI compute 32:08 The next billion-dollar opportunity: AI infrastructure orchestration 34:22 Where smart investors are looking beyond AI applications 37:35 Edge AI explained: Why AI is moving onto devices 40:43 Why AI chips need hardware & software co-design 44:18 The race to build the operating system for Edge AI 48:33 Self-driving cars, robots & the future of physical AI 52:08 Quantum computing: Beyond the hype 55:25 Quantum computing investment opportunities & "picks and shovels" 58:44 Practical AI advice for CIOs, business leaders & enterprises 1:02:02 Will AI replace humans? The future of human-AI collaboration 1:04:42 Final thoughts Connect with Ankur: LinkedIn: https://www.linkedin.com/in/saxenaankur/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Robin Hanson believes the future of AI is far stranger than most people imagine. In this episode, economist, futurist, and The Age of Em author Robin Hanson explains one of the biggest questions humanity has faced: What happens after humans? Instead of viewing AI as humanity's greatest threat, Hanson argues we should think of AI as our descendants. The conversation looks at why AI replacing humans may be part of civilization's natural evolution, why capitalism and competition aren't disappearing, and how cultural evolution, not technology, may be humanity's biggest existential challenge. We also examine the Great Filter, the future of work, AI regulation, software engineering, technological progress, fertility decline, civilization collapse, AI governance, and why Robin believes our greatest risk isn't AI taking over, but humanity losing its ability to evolve culturally. If you're interested in the future of AI, artificial intelligence, AGI, economics, civilization, technology, and what comes after humanity, this conversation will challenge many of your assumptions. Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, and digital transformation. In this episode: 00:00 Intro 01:00 AI will eventually replace humanity 01:36 Robin Hanson’s background 02:20 The future of civilization 03:22 The Age of Em explained 06:03 Why brain emulation changes everything 07:24 Capitalism isn't going away 11:18 Is humanity actually progressing? 13:10 The Great Filter explained 18:17 Why AI isn't the Great Filter 22:02 AI, technological acceleration & the next 20 years 24:24 Will AI leave people behind? 29:04 How to survive technological disruption 33:08 Why AI is humanity's descendants 40:23 Cultural evolution is breaking 47:12 Why civilization is becoming maladaptive 55:06 Is modern society quietly declining? 01:00:45 Can AI solve civilization's biggest problem? 01:07:01 AI risk vs AI progress 01:12:00 Should AI be regulated? 01:17:03 The US, China & the AI race 01:22:26 AI's economic impact 01:25:19 Advice for business leaders 01:30:45 AI's biggest opportunity for humanity 01:38:48 What gives Robin Hanson hope 01:42:24 Final thoughts Connect with Robin: X: https://x.com/robinhanson Facebook: https://www.facebook.com/robin.hanson.754/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG