TechFirst with John Koetsier

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

  1. 2D AGO

    Robot reasoning: why data is not enough

    Robots aren’t just software. They’re AI in the physical world. And that changes everything. In this episode of TechFirst, host John Koetsier sits down with Ali Farhadi, CEO of Allen Institute for AI, to unpack one of the biggest debates in robotics today: Is data enough, or do robots need structured reasoning to truly understand the world? Ali explains why physical AI demands more than massive datasets, how concepts like reasoning in space and time differ from language-based chain-of-thought, and why transparency is essential for safety, trust, and human–robot collaboration. We dive deep into MOMO Act, an open model designed to make robot decision-making visible, steerable, and auditable, and talk about why open research may be the fastest path to scalable robotics. This conversation also explores: • Why reasoning looks different in the physical world • How robots can project intent before acting • The limits of “data-only” approaches • Trust, safety, and transparency in real-world robotics • Edge vs cloud AI for physical systems • Why open-source models matter for global AI progress If you’re interested in robotics, embodied AI, or the future of intelligent machines operating alongside humans, this episode is a must-watch. 👤 Guest Ali Farhadi CEO, Allen Institute for AI (AI2) Professor, University of Washington Former Apple researcher ⸻ 👉 Subscribe for more conversations like this: https://techfirst.substack.com ⸻ 00:00 – Plato vs Aristotle… in robotics? 00:55 – What “reasoning” means in the physical world 02:10 – How humans predict actions before they happen 03:45 – Why physical AI is fundamentally different from text AI 04:50 – The next revolution: AI in the real world 05:30 – What is MOMO Act? 06:20 – Chain-of-thought… for robots 07:45 – Trajectories as reasoning and robot transparency 08:55 – Trust, safety, and correcting robots mid-action 10:15 – Why predictability builds trust in machines 11:40 – What’s broken with data-only AI approaches 13:10 – Why reasoning + data isn’t an “either/or” 14:00 – Open sourcing robotics models: why it matters 15:20 – How closed AI slows innovation 16:45 – Global competition and open research 17:40 – What’s next for robotics reasoning models 18:20 – Can these models work across robot types? 19:30 – Temporal and spatial reasoning in MOMO 2 20:40 – Scaling robotics vs scaling LLMs 21:10 – Edge vs cloud AI for robots 22:20 – Specialized models, latency, and privacy 23:00 – Final thoughts on the future of physical AI

    22 min

  2. JAN 16

    Social humanoid robot for kids under $10,000

    Can we really build a $10,000 humanoid robot on open-source AI? In this episode of TechFirst, John Koetsier talks with Chris Kudla, CEO of Mind Children, about a radically different approach to humanoid robots. Instead of six-figure industrial machines built for factories or war zones, Mind Children is building small, safe, friendly social robots designed for kids, classrooms, and elder care. Meet Cody (MC-1), their first humanoid prototype. Cody is built on open-source AI from SingularityNET, combined with modular hardware, low-torque actuators, and a wheeled base designed for safety, affordability, and mass production. And there's some other AI bits and pieces from all the big name companies that you'd recognize. Mind Children's goal is ambitious: a $10,000 humanoid robot that families, schools, and care facilities can actually afford. In this conversation we explore: • Why social robots may be the real gateway to embodied AI • How Cody is designed for children and elder care instead of factories • Why wheels beat bipedal legs for safety, cost, and stability • How open-source AI and modular software stacks enable faster innovation • The emotional and ethical challenges of building companion robots • And what it takes to bring a humanoid robot to market at scale This is not sci-fi. This is the early blueprint of a future where humanoid robots are personal, affordable, and open-source. 00:00 – The $10,000 open-source humanoid question 01:58 – Meet Cody, the MC-1 prototype 04:10 – Why Cody is small, child-sized, and approachable 06:55 – Designing humanoids for kids and elder care 09:45 – Social robots vs industrial humanoids 12:40 – Wheels instead of legs and why that matters 16:05 – Low-torque actuators, safety, and toy-like design 19:20 – Modular hands, arms, and future upgrades 22:10 – Open-source AI and SingularityNET’s role 25:30 – On-robot vs cloud AI and why it matters 28:40 – Vision, LiDAR, and simulated world models 32:10 – Emotional awareness and social intelligence 35:10 – The $10K target and mass-production strategy 38:15 – The risks of attachment to robot companions 40:00 – Final thoughts on Cody and the future of social robots

    38 min

  3. JAN 14

    AI is now every UI: generative user interfaces explained

    Is AI really the new UI, or is that just another tech buzzphrase? Or ... is AI actually EVERY user interface now? In this episode of TechFirst, host John Koetsier sits down with Mark Vange, CEO & founder of Automate.ly and former CTO at Electronic Arts, to unpack what happens when interfaces stop being fixed and start being generated on the fly. They explore: • Why generative AI makes it cheaper to create custom interfaces per user • How conversational, auditory, and adaptive experiences redefine “UI” • When consistency still matters (cars, safety systems, frontline work) • Why AI doesn’t replace workers — but radically reshapes workflows • Whether browsers should become AI-native or stay neutral canvases • The unresolved risks around AI agents, payments, and control From hospitals using AI to speak Haitian Creole, to compliance forms that drop from hours to minutes, this conversation shows how every experience can become intelligent, contextual, and helpful. 👉 If you care about product design, AI, UX, or the future of software, this episode is for you. Subscribe for more conversations like this: https://techfirst.substack.com ⸻ 👤 Guest Mark Vange CEO & Founder, Automate.ly Former CTO, Electronic Arts Investor, serial entrepreneur, and builder focused on intent-driven, AI-native software ⸻ ⏱️ Chapter Markers 00:00 – Is AI the New UI? Why generative interfaces are reigniting the UI conversation 02:10 – The Hidden Cost of Traditional Interfaces Why one-size-fits-all software limits users 04:20 – When UIs Are Generated on Demand Adaptive experiences vs fixed screens and buttons 06:15 – Conversational & Multimodal Interfaces Why voice, audio, and language are all “UI” 08:30 – When Consistency Still Matters Safety, muscle memory, and shared interface conventions 10:45 – How Generative UIs Change Work AI as a collaborator, not a replacement 13:05 – Making Every Page an Application Why “dumb forms” and static sites are disappearing 15:10 – The Browser as the Ultimate Interface Neutral canvases vs AI-controlled environments 17:10 – AI Agents, Payments, and Control Why money is the hardest unsolved AI problem 19:25 – The Future of Multimodal UI Why UI goes far beyond pixels and screensIs AI really the new UI — or is that just another tech buzzphrase?

    21 min

  4. JAN 7

    Agent-first web: awesome or awful?

    The web is turning agentic. And that changes everything from shopping to search to SEO. In this episode of TechFirst, John Koetsier sits down with Dave Anderson (VP at ContentSquare + host of the “Tech Seeking Human” podcast) to unpack what happens when browsers and AI assistants don’t just answer … they do stuff. For you. On your behalf. From Atlas and agentic browsing to the growing backlash from retailers (hello, Amazon vs Perplexity), we explore who benefits, who loses, and what the internet becomes when agents are the default user. You’ll hear why retailers are nervous (security, margins, coupon hunting), why agent-first experiences might create “headless” retailers (like ghost kitchens, but for ecommerce), and why search is shifting from SEO to AI visibility. Plus: real talk about trusting agents with your credit card, hallucinations, and what it means if your agent can look indistinguishable from you. Guest Dave Anderson — VP, ContentSquare https://contentsquare.com Podcast: Tech Seeking Human https://www.techseekinghuman.ai Links & subscribe Subscribe for more conversations on tech, AI, and what’s next: https://techfirst.substack.com Transcripts always available here https://johnkoetsier.com 00:00 Agentic web: what changes when browsers “do stuff” 00:59 Meet Dave Anderson (VP + podcast host) 01:31 30,000 feet: why “agents” suddenly matter 03:48 The agent future John wanted 10 years ago 04:21 Why Amazon doesn’t want your agent shopping on Amazon 05:07 Ticketmaster, bots, and the security nightmare 06:26 Siri’s original promise vs today’s reality 08:31 Are agents just bots… or something different? 10:04 Retail fears: coupon hunting, margins, returns chaos 11:21 Can you trust an agent with your credit card? 11:59 Why retailers want their own agents (and control) 13:14 Amazon’s agent works… but is it the whole internet? 14:19 Ghost kitchens for retail: “headless” agent-first brands 15:17 Hugo Boss jacket test: agents vs manual search 16:40 Agents should talk to your finance agent 17:14 Kids + deepfakes: what even looks real anymore? 18:04 Is this corrosive to apps… or the web? 19:10 Online identity, anonymity, and agent verification 20:28 Two futures: human-first brands vs agent-first retail 21:19 Agentic browsers on your device: can they “look like you”? 22:51 Baseball vs golf: the best analogy for search now 24:44 Instant shopping problem: returns + missing “services layer” 26:10 AI weirdness: wrong names, wrong locations, shifting behavior 27:37 Agents beyond shopping: support is the sleeper win 29:49 Inventing the future: who adopts agents and who won’t 31:13 Will people get tired of AI and crave humans again? 31:45 Serendipity vs optimization: the restaurant debate 32:36 Wrap: nobody solved agents… but the shift is real

    33 min

  5. JAN 6

    World models: LLMs are not enough

    AI has mastered language, sort of. But the real world is way messier. In this episode of TechFirst, John Koetsier sits down with Kirin Sinha, founder and CEO of Illumix, to explore what comes after large language models: world models, spatial intelligence, and physical AI. They unpack why LLMs alone won’t get us to human-level intelligence, what it actually takes for machines to understand physical space, and how technologies born in augmented reality are now powering robotics, wearables, and real-world AI systems. This conversation goes deep on: • What “world models” really are — and why everyone from Fei-Fei Li to Jeff Bezos is betting on them • Why continuous video and outward-facing cameras are so hard for AI • The perception stack behind robots and smart glasses • Edge vs cloud compute — and why latency and privacy matter more than ever • How AR laid the groundwork for the next generation of physical intelligence If you’re building or betting on robotics, smart wearables, AR, or physical AI, this episode explains the infrastructure shift that’s already underway. Guest Kirin Sinha Founder & CEO, Illumix https://www.illumix.com 👉 Subscribe for more deep conversations on technology, AI, and the future: https://techfirst.substack.com 00:00 Raising the Bar on “Smart” Devices 01:07 Meet Kirin, Founder & CEO of Illumix 01:21 What Is a World Model — and Why It Matters 02:23 Why LLMs Alone Won’t Lead to AGI 03:46 From AR & the Metaverse to Physical AI 05:18 AR vs VR vs the Metaverse — Different Problems, Different Futures 06:32 Spatial Perception, Scene Understanding, and Contextual Intelligence 07:39 Why Continuous Video Is So Hard for Machines 08:39 The Camera Flip: From Selfie AI to World-Facing AI 09:58 Why Cameras Beat LiDAR for Wearables and Robots 10:27 Inside the Perception Stack 11:20 Edge vs Cloud Compute in Physical AI 12:37 Why On-Device Intelligence Matters for UX 13:52 SLMs, Efficiency, and the Limits of “Bigger Is Better” 15:11 Knowing What to Run — and When 16:06 Intent, Memory, and Real-Time AI Decisions 17:32 Physical Intelligence vs Digital Intelligence 18:39 Memory Palaces, Spatial Brains, and Human AI 19:39 Do We Need New Chips for Humanoid Robots? 20:26 How Chip Architectures Will Evolve for Physical AI 21:47 Privacy, On-Device Processing, and Trust 22:48 Final Thoughts on the Future of World-Aware AI

    22 min

  6. JAN 3

    Quantum computing, meet edge computing (thanks to diamonds)

    Quantum computers usually mean massive machines, cryogenic temperatures, and isolated data centers. But what if quantum computing could run at room temperature, fit inside a server rack — or even a satellite? In this episode of TechFirst, host John Koetsier sits down with Marcus Doherty, Chief Science Officer of Quantum Brilliance, to explore how diamond-based quantum computers work — and why they could unlock scalable, edge-deployed quantum systems. Marcus explains how nitrogen-vacancy (NV) centers in diamond act like atomic-scale qubits, enabling long coherence times without extreme cooling. We dive into quantum sensing, quantum machine learning, and why diamond fabrication — including the world’s first commercial quantum diamond foundry — could be the key to manufacturing quantum hardware at scale. You’ll also hear how diamond quantum systems are already being deployed in data centers, how they could operate in vehicles and satellites, and what the realistic roadmap looks like for logical qubits and real-world impact over the next decade. Topics include: • Why diamonds are uniquely suited for quantum computing • How NV centers work at room temperature • Quantum sensing vs. quantum computing • Manufacturing challenges and timelines • Quantum computing at the edge (satellites, vehicles, sensors) • The future of hybrid classical-quantum systems ⸻ 🎙 Guest Marcus Doherty Chief Science Officer, Quantum Brilliance Professor of Quantum Physics Army Reserve Officer 🌐 https://quantumbrilliance.com ⸻ 👉 Subscribe for more deep dives into the future of technology: https://techfirst.substack.com ⸻ 00:00 Diamonds and the next wave of quantum computing 01:20 Why diamond qubits work at room temperature 03:20 NV centers explained: defects that behave like atoms 05:05 How diamonds replace massive quantum isolation systems 06:40 Building the world’s first quantum diamond foundry 08:30 Defect-free diamonds, isotopes, and qubit engineering 10:15 Quantum sensing vs. quantum computing with diamonds 12:40 From desktop quantum systems to millions of qubits 14:25 Roadmap: logical qubits, timelines, and scale 16:10 Quantum computers at the edge: vehicles and satellites 18:10 Quantum machine learning and real-world deployments 19:50 The long game: why diamond quantum computing scales

    21 min

  7. 12/23/2025

    Will AI kill your job?

    Will AI kill your job? What happens to your job as AI gets smarter and companies keep laying people off even while profits rise? Will you still have a job? Will the job you have change beyond recognition? Scary questions, no? In this episode of TechFirst, host John Koetsier sits down with Nikki Barua, co-founder of Footwork and longtime founder, executive, and resiliency expert, to unpack what work really looks like in the age of AI. Layoffs are no longer just about economic downturns. Companies are growing, innovating, and still cutting staff, often because AI is enabling more output with less capacity. So what does that mean for you? Nikki argues the future doesn’t belong to those who simply “learn AI tools,” but to agentic humans: people who lead with uniquely human strengths and use AI to amplify their impact. This conversation explores: • Why today’s layoffs are different from past cycles • How AI is compressing jobs before creating new ones • What it means to move from doing work to directing outcomes • Why identity, curiosity, and agency matter more than certifications • How to rethink workflows instead of chasing shiny AI tools • The FLIP framework: Focus, Leverage, Influence, and Power This episode isn’t about fear. It’s about reinvention. If you’re wondering how to stay relevant, valuable, and resilient as AI reshapes work, this is the place to start. Guest Nikki Barua Co-founder, Footwork (Reinventing organizations with agentic AI) 👉 Subscribe for more conversations on AI, work, and the future of technology: https://techfirst.substack.com Chapters: 00:00 — Work in the AI Age: what happens to your job? 01:05 — Layoffs, AI, and why this cycle feels different 02:55 — “Don’t let AI have the last laugh” 04:45 — Profitable companies cutting jobs: what’s really happening 06:40 — The next 18–24 months: compression before reinvention 08:30 — AI’s impact on young workers and early careers 10:00 — What should you be doing right now? 11:20 — Why surface-level AI use won’t save your job 12:40 — The rise of the “agentic human” 14:20 — From doing to directing: humans + machines as partners 15:55 — Why certifications and training aren’t enough 17:10 — High-agency people win in the AI age 18:35 — The FLIP framework: Focus and identity 20:00 — Leverage: compounding capacity beyond automation 21:20 — Influence: trust, authenticity, and scaled impact 22:25 — Power: upgrading your personal operating system 23:40 — Two shifts that make this AI revolution different 25:05 — Tools vs workflows: where most people get it wrong 26:25 — The real blocker: old identities and fear of change 27:40 — Three steps to stay relevant in the AI age 28:40 — Final thoughts + wrap-up

    29 min

  8. 12/19/2025

    Building TARS from Interstellar in real life

    What if someone actually built TARS from Interstellar—and discovered it really could work? In this episode of TechFirst, host John Koetsier sits down with Aditya Sripada, a robotics engineer at Nimble, who turned a late-night hobby into a serious research project: a real, working mini-version of TARS, the iconic robot from Interstellar. Aditya walks through why TARS’s strange, flat form factor isn’t just cinematic flair—and how it enables both walking and rolling, one of the most energy-efficient ways for robots to move. We dive into leg-length modulation, passive dynamics, rimless wheel theory, and why science fiction quietly shapes real robotics more than most engineers admit. Along the way, Aditya explains what he learned by challenging his own assumptions, how the project connects to modern humanoid and warehouse robots, and why reliability—not flash—is the hardest problem in robotics today. He also previews his next ambitious project: building a real-world version of Baymax, exploring soft robotics and safer human-robot interaction. This is a deep, accessible conversation at the intersection of science fiction, physics, and real-world robotics—and a reminder that sometimes the ideas we dismiss as “impossible” just haven’t been built yet. ⸻ Guest Aditya Sripada Robotics Engineer, Nimble Researcher in legged locomotion, humanoids, and unconventional robot form factors ⸻ If you enjoyed this episode, subscribe for more deep dives into technology, robotics, and innovation: 👉 https://techfirst.substack.com ⸻ Chapters: 00:00 – TARS in Real Life: Why Interstellar’s Robot Still Fascinates Us 01:00 – Why Building TARS Seemed Physically Impossible 02:00 – From Weekend Hobby to Serious Robotics Research 03:00 – How Science Fiction Quietly Shapes Real Robot Design 04:00 – Walking vs Rolling: Why TARS Uses Both 05:00 – Why Simple Robots Can Beat Complex Humanoids 06:00 – Turning Legs into a Wheel: The Rolling Mechanism Explained 07:00 – Leg-Length Modulation and Passive Dynamics 08:00 – Inside the Actuators: Degrees of Freedom and Compact Design 09:00 – Why TARS’s Arms Don’t Really Make Sense 10:30 – Lessons Learned: Never Dismiss “Impossible” Ideas 12:00 – Rimless Wheels, Gaits, and Robotics Theory 13:00 – What This Project Taught Him at Nimble 14:00 – What “Super-Humanoid” Robots Actually Mean 15:30 – Why Reliability Matters More Than Flashy Demos 16:30 – TARS as a Research Platform, Not a Product 17:30 – From TARS to Baymax: Exploring Soft Robotics 19:00 – Can We Build Safer, Friendlier Humanoid Robots? 20:30 – What’s Next: Recreating Baymax in Real Life 21:30 – Final Thoughts and Wrap-Up

    21 min
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