TechFirst with John Koetsier

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

  1. 17時間前

    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分

  2. 3日前

    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分

  3. 2025/12/23

    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分

  4. 2025/12/19

    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分

  5. 2025/12/16

    AI is killing teen jobs faster

    AI is already reshaping the workforce. What about teenagers? Turns out, they might be more impacted than anyone else. After all, they're usually in low-skill entry-level jobs that AI can replace. The problem ... teens are losing their first experience with working, making money, and establishing an identity outside of their homes. In this episode of TechFirst, host John Koetsier speaks with Karissa Tang, a high school senior and UCLA research assistant, about her new study on how AI will impact teen employment. While most workforce studies focus on adults, Karissa analyzed the top 10 most popular teen jobs from cashiers to fast food workers and found something alarming: AI could reduce teen employment by nearly 30% by 2030. We dig into: • Which teen jobs are most vulnerable to AI and automation • Why cashiers and fast-food counter workers are hardest hit • The role of self-checkout, kiosks, and robots like Flippy • Which teen jobs appear safest (for now) • Why teens may be even more exposed to AI than adults • What schools, policymakers, and teens themselves can do next This is a must-watch conversation for parents, students, educators, and policymakers trying to understand how AI is reshaping early work experiences—and what it means for the next generation. 🎙 Guest Karissa Tang • Founder, Booted (board games company) • Research Assistant, UCLA • Former Intern, NSV Wolf Capital • High school senior and author of a 20-page research paper on AI & teen employment 📌 Subscribe & Stay Ahead If you want clear, thoughtful analysis on AI, technology, and the future of work, subscribe to TechFirst: 👉 https://techfirst.substack.com 00:00 – Will AI Kill Teen Jobs? 01:35 – Why a Teen Studied Teen Employment 03:10 – The Shocking 30% Job Loss Prediction 05:10 – Top 10 Teen Jobs Most at Risk 07:20 – Cashiers, Kiosks, and Self-Checkout 09:40 – Fast Food, Retail, and AI Displacement 12:15 – Which Teen Jobs Are Safest from AI 15:05 – Robots Like Flippy and the Future of Cooking Jobs 18:00 – Why Teen Jobs Are More Vulnerable Than Adult Jobs 21:40 – The Importance of Human Interaction at Work 25:10 – What Inspired the Research Study 29:30 – How the Data and Methodology Worked 33:40 – What Teens Can Do to Stay Employable 37:30 – Skills, AI Literacy, and Creating New Opportunities 41:00 – Final Thoughts on the Future of Teen Work

    20分

  6. 2025/12/09

    Terminator? This humanoid robot is literally built for war (and more)

    Are we about to create real life Terminators? Humanoid robots built for war? In this episode of TechFirst I talk with Sankaet Pathak, founder and CEO of Foundation, a California-based humanoid robot company that is not afraid of the defense market. We dig into why he is building humanoid robots that can work three shifts a day, how they plan to scale from dozens of robots to tens of thousands, and why he believes humanoid robots will one day build bases in Antarctica and cities on the moon. We also dive deep into military use cases. From logistics and infrastructure to “first body in” building breach operations, we explore how humanoid robots could change asymmetric warfare, deterrence, and who wins future conflicts. In this episode • Why humanoid robots are the next strategic advantage for countries and companies • How Foundation went from zero to a working production robot in about 18 months • The hardware secrets behind Phantom: actuators, efficiency, and safety • Why their robots can run almost 24 hours a day, three shifts at a time • The master plan: Antarctic bases, moon cities, and infinite robot labor • Why Sankaet thinks home robots should feel like a “genie in a bottle” • How humanoid robots may enter military operations and what that means for war • Whether robot soldiers lead to dominance, stalemate, or new forms of peace Guest: Sankaet Pathak, founder and CEO of Foundation Website: https://foundation.bot Subscribe to my Substack: https://techfirst.substack.com 00:00 – Are we about to build real life Terminators? 00:55 – Meet Sankaet Pathak and Foundation 02:08 – How Foundation built a production humanoid in 18 months 04:17 – Scaling plan: 40 robots today, 10,000 next year, 40,000 after 06:11 – Why manufacturing is still mostly manual and what they learned from Tesla 09:31 – The Foundation master plan: Antarctica, the moon, and infinite labor 14:21 – Phantom specs: size, strength, payload, and real factory work 15:36 – Actuators as robot muscles and why backdrivability matters 18:41 – Running three shifts a day and solving heat and durability 21:01 – Robot hands today and the tendon driven hands of tomorrow 23:40 – Why home robots should feel like a “genie in a bottle” 25:51 – Why the military needs humanoid robots 27:54 – Dangerous, boring, and impossible jobs robots should take over 29:22 – Drones, costs, and asymmetric warfare 32:18 – First body in and robots that can pull the trigger 33:16 – The future of war as “video game” and who wins 34:49 – Peace through strength and 100,000 robots as deterrent 35:22 – Final thoughts and what comes next for Foundation

    33分

  7. 2025/12/06

    AI agents in manufacturing: reshoring production?

    Is AI the secret sauce that lets the West deglobalize supply chains and bring factories back home? In this episode of TechFirst, I talk with Federico Martelli, CEO and cofounder of Forgis, a Swiss startup building an industrial intelligence layer for factories. Forgis runs “digital engineers” — AI agents on the edge — that sit on top of legacy machinery, cut downtime by about 30%, and boost production by roughly 20%, without ripping and replacing old hardware. We dive into how AI agents can turn brainless factory lines into adaptive, self-optimizing systems, and what that means for reshoring production to Europe and North America. In this episode, we cover: • Why intelligence is the next geopolitical frontier • How AI agents can reshore manufacturing without making it more expensive • Turning old, offline machines into data-driven, optimized systems • The two-layer model: integration first, vertical intelligence second • Why most manufacturing AI projects fail at integration, not algorithms • How Forgis raised $4.5M in 36 hours and chose its lead investor • Lean manufacturing 2.0: adding real-time data and AI to Toyota-style processes • Why operators stay in the loop (and why full autonomy is a bad idea… for now) • Rebuilding industrial ecosystems in Europe and North America, industry by industry • What Forgis builds next with its pre-seed round and where industrial AI is headed Guest: 👉 Federico Martelli, CEO & cofounder, Forgis (industrial intelligence for factories) 🔗 More on Forgis: https://forgis.com/ Host: 🎙 John Koetsier, TechFirst podcast 🔎 techfirst.substack.com If you enjoy this conversation, hit subscribe, drop a comment about where you think factories of the future will live, and share this with someone thinking about reshoring or industrial AI. 00:00 – Intro: AI, deglobalization, and the battle for industrial power 01:20 – Why intelligence is the next geopolitical frontier 02:13 – Applying AI agents to legacy machinery (not just new robots) 03:10 – Integration first, intelligence second: the “digital engineers” layer 03:58 – Early results: +20% production, –30% downtime 05:39 – The Palantir-style model: deep factory work, then recurring licenses 06:28 – Raising $4.5M in 36 hours and choosing Redalpine 08:17 – Lean manufacturing, Toyota, and giving operators superpowers (not replacing them) 10:18 – Big picture: reshoring production to Europe, the US, and Canada 12:48 – Competing with China’s dense manufacturing ecosystems 15:29 – What Forgis’ digital engineers actually do on the shop floor 17:06 – How Forgis will use the pre-seed round: sales, product, then tech 18:32 – Flipping the traditional stack: sales → product → tech 19:22 – Wrap-up and what’s next for industrial intelligence

    19分

  8. 2025/12/04

    Paypal for agents: welcome to agentic commerce

    AI agents can already write code, build websites, and manage workflows ... but they still can’t pay for anything on their own. That bottleneck is about to disappear. In this episode of TechFirst with John Koetsier, we sit down with Jim Nguyen, former PayPal exec and cofounder/CEO of InFlow, a new AI-native payments platform launching from stealth. InFlow wants to give AI agents the ability to onboard, pay, and get paid inside the flow of work, without redirects, forms, or a human typing in credit card numbers. We talk about: • Why payments — not intelligence — are the missing link for AI agents • How agents become a new kind of customer • What guardrails and policies keep agents from spending all your money • Why enterprises will need HR for agents, budgets for agents, and compliance systems for agents • The future of agent marketplaces, headless ecommerce, and machine-speed commerce • How InFlow plans to become the PayPal of agentic systems If AI agents eventually hire, fire, transact, and manage entire workflows, someone has to give them wallets. This episode explores who does it, how it works, and what it means for the economy. 👀 Full episode transcript + articles at: https://johnkoetsier.com 🔎 Deeper insight in my Substack at techfirst.substack.com 🎧 Subscribe to the podcast on any audio platforms 00:00 — AI agents can’t pay yet 01:00 — Why agents need financial capabilities 02:45 — Developers as the first use case 04:15 — Agents that build AND provision software 06:00 — Agents as real customers with budgets 07:30 — Payments infrastructure is the missing layer 09:00 — Machine-speed commerce and GPU allocation 10:15 — From RubyCoins to PayPal to agentic payments 12:00 — Policy guardrails: the child debit card analogy 14:00 — Accountability: every agent must be “sponsored” 15:00 — HR, finance, and compliance systems for agents 16:45 — Agent marketplaces and future gig platforms 18:15 — Headless commerce: ghost kitchens for AI agents 20:00 — Agents are the new apps 21:15 — Amazon pushback and optimizing for revenue 22:45 — Why agent-optimized platforms will emerge 23:30 — Voice commerce, invisible ordering, and wallets 24:15 — Final thoughts: building the rails for agent commerce

    24分
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番組について

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

情報

  • クリエイター
    John Koetsier
  • 配信期間
    19年 - 26年
  • エピソード
    355
  • 制限指定
    不適切な内容を含まない
  • Copyright
    © John Koetsier
  • 番組のWebサイト
    TechFirst with John Koetsier

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