NEXT with John Koetsier

John Koetsier

Deep tech conversations with key innovators in AI, robotics, and smart matter ...

  1. -5 ч

    AI can now edit DNA and create deepfake viruses

    AI is moving beyond text, images, and code. Now it’s learning to read and write -- shall we say program -- DNA.In this episode of NEXT, John Koetsier talks with Eric Nguyen, co-founder and CEO of Radical Numerics, about the rapidly emerging world of biological AI.Nguyen and his team helped create Evo and Evo 2, generative foundation models for DNA, and are now working toward what they call “general biological intelligence”: AI systems capable of understanding biology across DNA, gene expression, methylation, proteins, and other biological signals.The potential upside is enormous. These systems could help scientists detect cancer earlier, develop treatments for antibiotic-resistant superbugs, understand disease more deeply, and eventually design countermeasures to emerging biological threats on demand.But the same capabilities introduce serious risks.Nguyen explains how AI could potentially generate biological sequences that retain dangerous functions while evading traditional sequence-matching detection systems ... essentially creating biological “deepfakes.” He also discusses why AI labs need to develop biodefense capabilities alongside increasingly powerful biological design tools.The conversation covers DNA foundation models, AI-generated viruses, biosecurity, pathogen detection, wastewater surveillance, attribution of biological threats, antimicrobial resistance, cancer detection, open-source versus closed-source biological AI, and why biology may be the next major frontier for artificial intelligence.00:00 AI-designed DNA and “deepfake” viruses00:21 AI is moving into biology00:55 Meet Eric Nguyen of Radical Numerics01:20 Why DNA is a language01:39 Teaching AI to read and write DNA02:54 What happens when AI can create biological systems?03:15 The promise and risks of programmable DNA04:32 The medical upside of AI-driven biology04:58 Moving beyond single-molecule drug discovery06:30 Can AI model the complexity of the human body?06:59 Biology has more data than we know how to use08:38 Where all the DNA data comes from09:12 The dangerous side of AI-generated biology10:01 What is a “deepfake virus”?12:41 Could AI make pathogens more dangerous?14:36 Putting AI biodefense on the front lines16:56 The three pillars of biodefense18:22 On-demand treatments for new diseases19:11 How close is this future?21:53 Why biodefense capabilities are falling behind24:36 Should powerful DNA models be open source?25:40 How Evo and Evo 2 were made safer26:49 Why Radical Numerics is keeping Omni closed27:55 AI-generated bacteriophages and superbugs29:23 Balancing breakthrough biology with biosecurity30:53 Using AI to detect cancer earlier32:08 Why cancer detection needs multiple biological signals33:49 “Sensor fusion” for biology34:24 Why a holistic view of medicine matters

  2. 30 июл.

    Do we really need 400 humanoid robot companies?

    Why aren’t hundreds of millions of intelligent robots already operating in the physical world? In this episode of NEXT with John Koetsier, John speaks with Seth Winterroth, partner at Eclipse, about the rapidly changing robotics investment landscape, the rise of physical AI, and the race to build the next generation of autonomous machines. They explore whether the world really needs hundreds of humanoid robotics companies, why timing matters as much as technology, and why some robotics startups may need to build the entire stack ... from hardware and embedded software to AI models, evaluation systems, and deployment infrastructure. The conversation also covers Genesis AI, Wayve, Project Prometheus, Apptronik, Figure, 1X, autonomous vehicles, delivery drones, industrial automation, surgical robotics, and the future of robots in the home. Topics include: • Why robots still aren’t widely deployed • The five forces driving robotics investment • Whether 400 humanoid robotics companies are too many • Full-stack versus platform-based robotics strategies • The challenge of achieving reliability and safety • When useful home robots may finally arrive • Why autonomous vehicles are already robots • The industries likely to adopt robotics first • The future of manufacturing, logistics, transportation, and surgery • What the next major robotics inflection point could be Seth Winterroth is a partner at Eclipse, an investment firm focused on companies transforming physical industries. Eclipse has backed robotics and automation companies including Genesis AI, Wayve, MiND Robotics, Foxglove, and Third Wave Automation. Subscribe to NEXT for more conversations about AI, robotics, emerging technology, and the companies shaping the future. 00:00 Why aren’t robots everywhere yet? 00:37 Introducing Seth Winterroth 01:03 The robotics investment landscape 02:00 Seth’s background in applied robotics 03:01 The five forces accelerating robotics 04:04 Are there too many humanoid robot companies? 05:00 Creative destruction in robotics 06:02 How investors pick the winners 06:38 Why robotics companies need velocity 07:00 The danger of being too early or too late 07:51 How Wayve benefited from entering later 08:36 Project Prometheus and the $10 billion seed round 09:05 Why Genesis AI is building full stack 10:01 Full-stack robotics versus foundation-model platforms 11:03 The dirty secret: Where are all the robots? 12:03 Reliability, safety, and deployment friction 12:39 The challenge of vertical integration 14:02 What robotics companies should build themselves 15:03 Capital requirements and the robotics J-curve 16:01 How robotics companies can scale rapidly 16:39 When humanoid robots may reach the market 17:04 Figure, 1X NEO, Unitree, and AgiBot 18:24 A broader definition of robotics 19:04 Are cameras and dishwashers robots? 19:39 Autonomous vehicles as embodied AI 20:23 Why transportation autonomy could be transformational 21:05 Why humanoids still have a long way to go 21:44 One general-purpose robot or many specialized machines? 22:35 What will make home robots successful? 23:39 Finding the minimum viable home robot 24:20 Physical and digital products 25:04 Why the App Store model matters for robotics 26:05 How robots will gain new capabilities over time 26:35 The brutal economics of consumer robotics 27:12 Consumers buy outcomes, not robots 27:48 Robotics beyond humanoids 28:18 Kiva Systems and the modern robotics era 29:05 Why constrained environments win first 30:02 Robotics in automotive manufacturing and logistics 31:02 Eclipse’s robotics portfolio 31:31 When robots will begin walking among us 32:03 The next major robotics inflection point 32:42 Escaping the trough of disillusionment 33:29 Why autonomous transportation is nearly solved 34:04 How self-driving changes cities and society 34:36 The future of robotic surgery 35:01 Delivery drones and regulatory barriers 35:39 Closing thoughts

  3. 14 июл.

    Rhoda AI: 1000X less training data required?

    Can robots learn from the internet the same way ChatGPT learned from text? In this episode, Andrew Wooten, co-founder of Rhoda AI, explains why his company believes the future of robotics isn’t collecting millions of hours of robot data ... it’s learning from internet-scale video. Instead of relying on traditional vision-language-action (VLA) models that require enormous training datasets, Rhoda’s approach teaches robots physical intuition by predicting the future through video. We also explore why, in Andrew's opinion, warehouses and factories will likely be the first major market for humanoid robots (not homes!), why Rhoda chose a wheel-based humanoid design, how language models fit into physical AI, and how the company’s robots can learn complex tasks with just 8–10 hours of training data instead of 10,000+ hours. If you’re interested in robotics, AI, automation, or the future of manufacturing, this conversation offers a fascinating look at where physical AI is heading. In this episode: * Why warehouses beat homes as the first market for humanoid robots * Why Rhoda chose wheels instead of legs * The biggest limitation of today’s robot AI models * How internet-scale video teaches robots physics * Why predicting the future helps robots manipulate the real world * Edge AI vs. cloud robotics * The role of LLMs in controlling robots * How Rhoda cut robot training from 10,000+ hours to just 8–10 hours * When zero-shot robot learning could become reality Guest Andrew Wooten Co-founder, Rhoda AI Website: https://rhoda.ai 00:00 Why Humanoid Robots Don’t Have Wheels 00:18 Can Robots Learn From Internet Video? 00:42 Best Use Cases for Humanoid Robots 02:10 Why Warehouses and Factories Come First 04:02 The Economic Impact of Robotics 05:00 Home Robots vs. Industrial Robots 06:05 Why Rhoda AI Chose Wheels 08:00 Building a General-Purpose Robot 09:55 Why Full-Stack Robotics Companies Have an Advantage 10:40 The Evolution of Physical AI 12:20 Why Vision-Language-Action Models Fall Short 14:05 Training Robots With Internet-Scale Video 16:05 How Rhoda AI’s Video-Action Model Works 17:25 Edge AI vs. Cloud Computing 19:05 How Robots Develop Physical Intuition 20:40 Predicting the Near Future in Real Time 22:00 Can Robots Build a Subconscious? 23:10 Using Language Models to Control Robots 25:15 Rhoda AI’s Hardware Strategy 26:20 The Biggest Problems With Today’s Humanoids 28:20 When Will Robots Truly Learn on the Job? 30:05 Training Complex Tasks in 8–10 Hours 31:15 Zero-Shot Robot Learning and What Comes Next

  4. 19 июн.

    Is AI killing jobs or are CEOs using it as an excuse?

    Is AI really causing mass layoffs or are CEOs just using AI as a convenient excuse? In this episode, John Koetsier talks with longtime tech journalist, columnist, author, and podcaster Mike Elgan about why the “AI is killing jobs” narrative may be overblown. Elgan argues that many companies are engaging in AI washing: blaming layoffs on AI to make cost-cutting look like innovation. The conversation goes deep into the future of work, why every major technology shift creates fear before new opportunities emerge, how AI will change education and human skills, and why humanoid robots may be more hype than practical reality. They also explore Elgan’s concept of the attachment economy: a future where AI products don’t just compete for our attention, but for our emotional bonds. Guest Mike Elgan Tech journalist, columnist, author, and podcaster Host of Superintelligent Author of The Attachment Economy on Substack Subscribe for more conversations on AI, robots, innovation, and the future of technology: https://techfirst.substack.com Chapters:00:00 AI, layoffs, and whether AI is really to blame01:00 Meet Mike Elgan02:00 Why people believe AI will cause mass job loss03:00 AI washing and layoffs as a CEO “fig leaf”05:00 Techno-utopian claims about AI replacing work06:00 Why AI layoffs often don’t pass the logic test08:00 Past tech revolutions and new job creation09:00 Companies that lay off because of AI “lack imagination”11:00 Why new industries can create more jobs13:00 Nobody can predict where AI will lead15:00 Why the speed of AI change feels different16:00 AI, robotics, and fear about the future of work17:00 AI natives and generational change19:00 Why humans treat talking AI like a person20:00 Education when facts are instantly available22:00 Cursive, typing, and speech-to-text24:00 Humanoid robots in the home25:00 Human work, creativity, and future value26:00 Why human connection may become more valuable27:00 Are humanoid robots a dumb idea?29:00 Specialized robots vs. humanoid robots31:00 The attachment economy after the attention economy32:00 AI products designed to create emotional attachment34:00 Relationship AI, robot pets, and illusion35:00 Why chatty AI feels conscious36:00 The human brain, AI illusion, and caution37:00 Closing thoughts with Mike Elgan

  5. 17 июн.

    Robots in schools? Interviewing Chris Chen from Faraday Future

    Humanoid robots are often pitched as factory workers, warehouse assistants, or home helpers. But what if education becomes their biggest opportunity? In this episode, Faraday Future co-CEO Chris Chen explains why K-12 schools, STEM programs, and university research labs could be among the first large-scale adopters of humanoid robots and robot dogs. Chris shares why Faraday Future believes we’re at the beginning of an “iPhone moment” for robotics, how the company plans to deliver nearly 1,000 robots this year, and why physical AI represents the next major evolution beyond today’s large language models. We also discuss: • Why humanoid robot adoption is accelerating worldwide • The transition from digital AI to physical AI • How robots could help teach coding, STEM, and AI literacy • Security, hospitality, and inspection use cases already being deployed • Why Chris believes robotics could become a much larger market than automobiles • Building a robotics ecosystem powered by data, developers, and AI If you’re interested in AI, robotics, education, automation, or the future of work, this conversation offers a fascinating look at where the industry is headed next. Guest: Chris Chen Co-CEO, Faraday Future Nasdaq: FFAI Subscribe for more conversations with the leaders shaping the future of technology: https://techfirst.substack.com Chapters: 00:00 Introduction: Humanoid Robots in Education 00:31 Faraday Future’s Vision for Physical AI Infrastructure 01:42 The Goal of 1,000 Robot Deliveries 02:22 Why Humanoid Robot Manufacturing Is Accelerating 03:37 The Starting Point of the Humanoid Robotics Industry 04:14 From Digital AI to Physical AI 06:04 Why Schools Are a Key Robotics Market 06:52 The Three Factors Driving Robotics Adoption 07:15 K-12 Education, STEM Training, and Robotics Institutes 08:12 Getting Kids Interested in AI Instead of Games 09:04 The Future Demand for Robotics Technicians 09:43 Humanoids vs. Robot Dogs in Education 09:59 Will Every Student Have an AI Tutor? 10:30 Beyond Education: Security, Inspection, and Hospitality 11:14 Robot Dogs for Autonomous Security Patrols 11:50 The Coming Ecosystem for Robot Maintenance 12:06 Will Humanoid Robots Become Bigger Than Cars? 12:57 How Robots Could Impact Global GDP 13:28 Competing in the Exploding Robotics Industry 13:56 Building a Robotics Flywheel Through Data 15:01 The Team Behind Faraday Future Robotics 15:44 Where Faraday Future Will Be in One Year 16:03 Faraday Future, Robotics, EVs, and Web3 17:00 Closing Thoughts

  6. 10 июн.

    Goodbye wheelchairs. Hello Cruz: autonomous mobility pods

    What if airports had self-driving mobility pods that could safely navigate through crowds, just like something out of The Jetsons? Or the Pixar movie Wall-E? In this episode, John Koetsier sits down with Matthew Anderson, CEO of A&K Robotics, to explore the future of autonomous mobility. A&K Robotics is building AI-powered self-driving pods designed to help people navigate airports independently without relying on wheelchairs or staff assistance. But the real breakthrough isn’t just autonomy. It’s crowd navigation. Matthew explains why navigating dense, unpredictable crowds is one of the hardest problems in robotics, and how A&K’s “crowd-centric AI” could become foundational technology for airports, stadiums, smart cities, conferences, and even humanoid robots in the future. They also discuss: * Why airports are the perfect proving ground for robotics * The AI and sensor stack powering autonomous mobility * Directional sound systems inspired by The Sphere in Las Vegas * Scaling robotics startups from prototype to deployment * Raising an $8M Series A round * The personal story that inspired Matthew to build the company * Why the future of robotics depends on moving safely through human environments Guest: Matthew Anderson — CEO, A&K Robotics Company: A&K Robotics If you enjoy conversations about AI, robotics, startups, and the future of technology, subscribe for more interviews with founders and innovators shaping what’s next. Subscribe here: https://techfirst.substack.com 00:00 – Intro 00:30 – Meet A&K Robotics and the Vision for Autonomous Airport Mobility 01:20 – Why Crowd Navigation AI Is the Hardest Problem in Robotics 02:40 – Navigating Dense Airport Crowds and Passenger Flow 04:05 – Directional Sound and Designing a Better Airport Experience 05:50 – Building an “iPhone Experience” for Mobility Robots 06:30 – Sensors, LIDAR, and Operating Without GPS 07:20 – Fleet Management and Autonomous Operations in Airports 08:00 – Mapping Airports and Optimizing Routes Through Crowds 09:00 – Scaling the Business and Solving Systems Integration 10:00 – Charging, Docking Stations, and the Future Airport Network 10:45 – Raising an $8 Million Series A Round 11:20 – Customers: Vancouver International Airport and Aena 12:10 – Building a Polished Robotics Platform on Seed Funding 12:50 – Matthew Anderson’s Background in Robotics and Drones 14:00 – The Bigger Vision: Crowd Navigation for All Robots 14:40 – The Personal Story Behind the Company Mission 15:40 – Licensing Opportunities and the $5 Billion Airport Mobility Market 16:45 – Hiring, Scaling the Team, and Expanding Production 18:00 – Growing Up Hacking Robots and the AC/DC Story 19:10 – Why Building Robots Is Fun — and Why Accounting Wasn’t 20:40 – Final Thoughts and the Future of Autonomous Mobility

  7. 14 мая

    AI & education: disaster or destiny?

    Is AI in education a disaster ... or inevitable. We can easily see that AI is already changing education ... but is it making kids smarter, or just more dependent? In this episode of TechFirst, John Koetsier talks with Navin Gurnani, CEO of Code Ninjas, about how kids can learn to build with AI instead of simply asking ChatGPT for answers. They discuss why coding still matters in the age of vibe coding, how AI can actually strengthen creativity and critical thinking, and the foundational skills kids need to thrive in a future shaped by artificial intelligence. Navin explains how Code Ninjas teaches children as young as 8 to understand AI “behind the curtain,” develop grit and resilience, and gain the confidence to create games, apps, and even entrepreneurial projects powered by AI. The conversation also dives into: * Why passive AI use puts kids at a disadvantage * The mindset future-ready kids need * AI literacy for parents and children * How coding builds confidence and problem-solving skills * Why adaptability may become the most important human skill * The difference between using AI and leading with AI If you’re a parent, educator, entrepreneur, or simply curious about the future of learning, this episode is packed with practical insights about preparing kids for an AI-driven world. Guest Navin Gurnani — CEO, Code Ninjas Sponsor This episode is sponsored by Apprentice — the first AI agent built for agentic manufacturing. Chapters 0:00 Intro: Is AI destroying education? 1:00 Teaching kids to build with AI, not depend on it 2:00 AI, coding, games, and decision-making 3:00 Why understanding AI builds confidence 4:00 Passive AI users vs. AI creators 5:00 What kids learn at Code Ninjas 6:00 Grit, resilience, and problem-solving 8:00 Belt system and early wins 9:00 Building confidence through teaching others 10:00 AI literacy by age level 11:00 Teaching kids to use AI responsibly 12:00 Coding in the age of vibe coding 14:00 AI-assisted entrepreneurship for kids 15:00 Building future-ready mindsets 16:00 What a future-ready kid looks like 17:00 Adaptability and spotting AI mistakes 18:00 One thing parents should do now

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Deep tech conversations with key innovators in AI, robotics, and smart matter ...

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