TechFirst with John Koetsier

AI is devouring the planet’s electricity ... already using up to 2% of global energy and projected to hit 5% by 2030. But a Spanish-Canadian company, Multiverse Computing, says it can slash that energy footprint by up to 95% without sacrificing performance.They specialize in tiny AI: one model has the processing power of just 2 fruit fly brains. Another tiny model lives on a Raspberry Pi.The opportunities for edge AI are huge. But the opportunities in the cloud are also massive.In this episode of TechFirst, host John Koetsier talks with Samuel Mugel, Multiverse’s CEO, about how quantum-inspired algorithms can drastically compress large language models while keeping them smart, useful, and fast. Mugel explains how their approach -- intelligently pruning and reorganizing model weights -- lets them fit functioning AIs into hardware as tiny as a Raspberry Pi or the equivalent of a fly’s brain.They explore how small language models could power Edge AI, smart appliances, and robots that work offline and in real time, while also making AI more sustainable, accessible, and affordable. Mugel also discusses how ideas from quantum tensor networks help identify only the most relevant parts of a model, and how the company uses an “intelligently destructive” approach that saves massive compute and power.00:00 – AI’s energy crisis01:00 – A model in a fly’s brain02:00 – Why tiny AIs work03:00 – Edge AI everywhere05:00 – Agent compute overload06:00 – 200× too much compute07:00 – The GPU crunch08:00 – Smart matter vision09:00 – AI on a Raspberry Pi10:00 – How compression works11:00 – Intelligent destruction13:00 – General vs. narrow AIs15:00 – Quantum inspiration17:00 – Quantum + AI future18:00 – AI’s carbon footprint19:00 – Cost of using AI20:00 – Cloud to edge shift21:00 – Robots need fast AI22:00 – Wrapping up

Can AI give every creator their own virtual team? Maybe, thanks to a new platform from RHEI called Made, which offers Milo, an AI agent who becomes your creator director, Zara, an AI agent who is your community manager, and Amie, a third AI agent who takes on the role of relationship manager.And, apparently, more agents are coming soon.The creator economy is bigger than ever, but so is burnout. Tens of millions of creators are trying to do everything themselves: strategy, scripting, editing, community, distribution, data, thumbnails, research … the list never ends.What if creators didn’t have to do all of that?In this episode of TechFirst, I talk with Shahrzad Rafati, founder & CEO of RHEI, about Made, an agentic AI "dream team" designed to elevate human creativity, not replace it. We dig into: • Why so many creators burn out • How agentic AI workflows differ from ChatGPT-style prompting • What it means to be a “creator CEO” • How AI can manage community, analyze trends, and shape content strategies • The coming shift toward human taste, vision, and originality in a world of infinite AI content00:00 – Intro: Can AI give every creator a virtual team?01:03 – Why the creator economy is burning out02:25 – The “creator CEO” problem: too many hats, not enough time04:36 – Introducing MAID and its AI agents05:34 – Milo: AI creative director (ideas, research, thumbnails, metadata)06:18 – Zara: AI community manager and fan engagement07:53 – Why this is different from just using ChatGPT09:46 – Alignment, personalization, and agentic workflows12:21 – Multi-platform support: YouTube, TikTok, Instagram and more13:34 – How onboarding works and how the system learns your style16:33 – What this means for creators — and for the future of work18:52 – Does *she* use her own virtual AI team? (Yes.)20:15 – MAID for teams and enterprise clients21:17 – Closing thoughts: AI, creativity, and the human signal

What happens when Amazon, NVIDIA, and MassRobotics team up to merge generative AI with robotics?In this episode of TechFirst we chat with Amazon's Taimur Rashid, Head of Generative AI and Innovation Delivery. We talk about "physical AI" ... AI with spatial awareness and the ability to act safely and intelligently in the real world.We also chat about the first cohort of a new accelerator for robotics startups.It's sponsored by Amazon and NVIDIA, run by MassRobotics, and includes startups doing autonomous ships, autonomous construction robots, smart farms, hospital robots, manufacturing and assembly robots, exoskeletons, and more.We talk about:- Why “physical AI” is the missing piece for robots to become truly useful and scalable- How startups in Amazon’s and NVIDIA’s new Physical AI Fellowship are pushing the limits of robotics from exoskeletons to farm bots- What makes robotic hands so hard to build- The generalist vs. specialist debate in humanoid robots- How AI is already making Amazon warehouses 25% more efficientThis is a deep dive into the next phase of AI evolution: intelligence that can think, move, and act.⸻00:00 — Intro: Is physical AI the missing piece?00:46 — What is “physical AI”?02:30 — How LLMs fit into the physical world03:25 — Why safety is the first principle of physical AI04:20 — Why physical AI matters now05:45 — Workforce shortages and trillion-dollar opportunities07:00 — Falling costs of sensors and robotics hardware07:45 — The biggest challenges: data, actuation, and precision09:30 — The fine-grained problem: how robots pick up a berry vs. an orange11:10 — Inside the first Physical AI cohort: 8 startups to watch12:25 — Bedrock Robotics: autonomy for construction vehicles12:55 — Diligent Robotics: socially intelligent humanoids in hospitals14:00 — Generalist vs. specialist robots: why we’ll need both15:30 — The future of physical AI in healthcare and manufacturing16:10 — How Amazon is already using robots for 25% more efficiency17:20 — The fellowship’s future: expanding beyond startups18:10 — Wrap-up and key takeaways

Artificial general intelligence (AGI) could be humanity’s greatest invention ... or our biggest risk.In this episode of TechFirst, I talk with Dr. Ben Goertzel, CEO and founder of SingularityNET, about the future of AGI, the possibility of superintelligence, and what happens when machines think beyond human programming.We cover: • Is AGI inevitable? How soon will it arrive? • Will AGI kill us … or save us? • Why decentralization and blockchain could make AGI safer • How large language models (LLMs) fit into the path toward AGI • The risks of an AGI arms race between the U.S. and China • Why Ben Goertzel created Meta, a new AGI programming language📌 Topics include AI safety, decentralized AI, blockchain for AI, LLMs, reasoning engines, superintelligence timelines, and the role of governments and corporations in shaping the future of AI.⏱️ Chapters00:00 – Intro: Will AGI kill us or save us?01:02 – Ben Goertzel in Istanbul & the Beneficial AGI Conference02:47 – Is AGI inevitable?05:08 – Defining AGI: generalization beyond programming07:15 – Emotions, agency, and artificial minds08:47 – The AGI arms race: US vs. China vs. decentralization13:09 – Risks of narrow or bounded AGI15:27 – Decentralization and open-source as safeguards18:21 – Can LLMs become AGI?20:18 – Using LLMs as reasoning guides21:55 – Hybrid models: LLMs plus reasoning engines23:22 – Hallucination: humans vs. machines25:26 – How LLMs accelerate AI research26:55 – How close are we to AGI?28:18 – Why Goertzel built a new AGI language (Meta)29:43 – Meta: from AI coding to smart contracts30:06 – Closing thoughts

What changes when robots deliver everything?Starship Technologies has already completed 9 million autonomous deliveries, crossed roads over 200 million times, and operates thousands of sidewalk delivery robots across Europe and the U.S. Now they’re scaling into American cities ... and they say they’re ready to change your worldIn this episode of TechFirst, I speak with Ahti Heinla, co-founder and CEO of Starship and co-founder of Skype, about: - How Starship’s robots navigate without GPS - What makes sidewalk delivery better than drones - Solving the last-mile problem in snow, darkness, and dense cities - How Starship is already profitable and fully autonomous - What it all means for the future of commerce and city lifeHeinla says:“Ten years ago we had a prototype. Now we have a commercial product that is doing millions of deliveries.”Watch to learn why the future of delivery might roll ... as well as fly.🔗 Learn more: https://www.starship.xyz🎧 Subscribe to TechFirst: https://www.youtube.com/@johnkoetsier00:00 - Intro: What changes when robots deliver everything?01:37 - Meet Starship: 9 million robot deliveries and counting02:45 - Why it took 10 years to go from prototype to product05:03 - When robot delivery becomes normal (and where it already is)08:30 - How Starship robots handle cities, traffic, and construction11:20 - Snow, darkness, and all-weather autonomy13:19 - Reliability, unit economics, and competing with human couriers16:23 - Inside the tech: sensors, AI, and why GPS isn’t enough18:03 - Real-time mapping, climbing curbs, and reaching your door19:54 - How Starship scales without local depots or chargers22:04 - How city life and commerce change with robot delivery25:53 - Do robots increase customer orders? (Short answer: yes)27:05 - Hot food, Grubhub integration, and thermal insulation28:26 - Will Starship use drones in the future?29:38 - What U.S. cities are next for robot delivery?

Imagine a quantum computer with a million physical qubits in a space smaller than a sticky note.That’s exactly what Quantum Art is building. In this TechFirst episode, I chat with CEO Tal David, who shares his team’s vision to deliver quantum systems with: • 100x more parallel operations • 100x more gates per second • A footprint up to 50x smaller than competitorsWe also dive into the four key tech breakthroughs behind this roadmap to scale Quantum Art's computer:1. Multi-qubit gates capable of 1,000 2-qubit operations in a single step2. Optical segmentation using laser-defined tweezers3. Dynamic reconfiguration of ion cores at microsecond speed4. Modular, ultra-dense 2D architectures scaling to 1M+ qubitsWe also cover:- How Quantum Art plans to reach fault tolerance by 2033- Early commercial viability with 1,000 physical qubits by 2027- Why not moving qubits might be the biggest innovation of all- The quantum computing future of healthcare, logistics, aerospace, and energy🎧 Chapters00:00 – Intro: 1M qubits in 50mm²01:45 – Vision: impact in business, humanity, and national tech03:07 – Multi-qubit gates (1,000 ops in one step)05:00 – Optical segmentation with tweezers06:30 – Rapid reconfiguration: no shuttling, no delay08:40 – Modular 2D architecture & ultra-density10:30 – Physical vs logical qubits13:00 – Quantum advantage by 202716:00 – Addressing the quantum computing skeptics17:30 – Real-world use cases: aerospace, automotive, energy19:00 – Why it’s called Quantum Art👉 Subscribe for more deep tech interviews on quantum, robotics, AI, and the future of computing.

Are humanoid robots distracting us from the real unlock in robotics ... hands? In this TechFirst episode, host John Koetsier digs into the hardest (and most valuable) problem in robotics: dexterous manipulation. Guest Mike Obolonsky, Partner at Cortical Ventures, argues that about $50 trillion of global economic activity flows through “hands work,” yet manipulation startups have raised only a fraction of what locomotion and autonomy companies have. We break down why hands are so hard (actuators, tactile sensing, proprioception, control, data) and what gets unlocked when we finally crack them.What we'll talk through ...• Why “navigation ≠ manipulation” and why most real-world jobs need hands• The funding mismatch: billions to autonomy & humanoids vs. comparatively little to hands• The tech stack for dexterity: actuators, tactile sensors (pressure, vibration, shear), feedback, and AI• Grasping vs. manipulation: picking, placing, using tools (e.g., dishwashers to scalpels)• Reliability in the wild: interventions/hour, wet/greasy plates, occlusions, bimanual dexterity• Practical paths: task-specific grippers, modular end-effectors, and “good enough” today vs. general purpose tomorrow• The moonshot: what 70–90% human-level hands could do for productivity on Earth ... and off-planetChapters00:00 Intro—are we underinvesting in robotic hands?01:10 Why hands matter more than legs (economics of manipulation)04:30 Funding realities: autonomy & humanoids vs. hands08:40 Locomotion progress vs. manipulation bottlenecks12:10 Teleop now, autonomy later—how data gets gathered14:20 What’s missing: actuators, tactile sensing, proprioception17:10 Perception limits in the real world (wet dishes, occlusions)22:00 General-purpose dexterity vs. task-specific ROI26:00 Startup landscape & reliability (interventions/hour)29:00 Modular end-effectors and upgrade paths30:10 The moonshot: productivity explosion when hands are solvedWho should watchRobotics founders, VCs, AI researchers, operators in warehousing & manufacturing, and anyone tracking humanoids beyond the hype.If you enjoyed thisSubscribe for more deep-tech conversations, drop a comment with your take on the “hands vs. legs” debate, and share with someone building robots.Keywordsrobotic hands, dexterous manipulation, humanoid robots, tactile sensing, actuators, proprioception, warehouse automation, AI robotics, Cortical Ventures, TechFirst, John Koetsier, Mike Obolonsky#Robotics #AI #Humanoids #RobotHands #Manipulation #Automation #TechFirst

Are humanoid robots the future… or a $100B mistake?Over 100 companies—from Meta to Amazon—are betting big on humanoids. But are we chasing a sci-fi dream that’s not practical or profitable?In this TechFirst episode, I chat with Bren Pierce, robotics OG and CEO of Kinisi Robots. We cover: - Why legs might be overhyped - How LLMs are transforming robots into agents - The real cost (and complexity) of robotic hands - Why warehouse robots work best with wheels - The geopolitical robot arms race between China, the US, and Europe - Hot takes, historical context, and a glimpse into the next 10 years of AI + robotics.Timestamps:0:00 – Are humanoids a dumb idea?1:30 – Why legs might not matter (yet)5:00 – LLMs as the real unlock12:00 – The hand is 50% of the challenge17:00 – Speed limits = compute limits23:00 – Robot geopolitics & supply chains30:00 – What the next 5 years looks likeSubscribe for more on AI, robotics, and tech megatrends.

The future could be much healthier for both farmers and everyone who eats, thanks to farm robots that kill weeds with lasers. In this episode of TechFirst, we chat with Paul Mikesell, CEO of Carbon Robotics, to discuss groundbreaking advancements in agricultural technology. Paul shares updates since our last conversation in 2021, including the launch of LaserWeeder G2 and Carbon's autonomous tractor technology: AutoTractor. LaserWeeder G2 quick facts: - Modular design: Swappable laser “modules” that adapt to different row sizes (80-inch, 40-inch, etc.) - Laser hardware: Each module has 2 lasers; a standard 20-foot machine = 12 modules = 24 lasers - Laser precision: Targets the plant’s meristem (≈3mm on small weeds) with pinpoint accuracy - Weed kill speed: 20–150 milliseconds per weed (including detection + laser fire) - Throughput: 8,000–10,000 weeds per minute (Gen 2, up from ~5,000/min on Gen 1) - Coverage rate: 3–4 acres per hour on the 20-foot G2 model - ROI timeline: Farmers typically achieve payback in under 3 years - Yield impact: Up to 50% higher yields in some conventional crops due to eliminating herbicide damage - Price: Standard 20-foot LaserWeeder G2 = $1.4M, larger models scale from there - Global usage: Units in the U.S. (Midwest corn & soy, Idaho & Arizona veggies) and Europe (Spain, Italy tunnel farming)We chat about how these innovations are transforming weed control and farm management with AI, computer vision, and autonomous systems, the precision and efficiency of laser weeding, practical challenges addressed by autonomous tractors, and the significant ROI and yield improvements for farmers. This is a must-watch for anyone interested in the future of farming and sustainable agriculture.00:00 Introduction to TechFirst and Carbon Robotics01:10 The Science Behind Laser Weeding05:46 Introducing Laser Weeder 2.006:39 Modular System and New Laser Technology09:26 Manufacturing and Cost Efficiency11:47 ROI and Benefits for Farmers13:24 Laser Weeder Specifications14:08 Performance and Efficiency14:49 Introduction to AutoTractor17:23 Challenges in Autonomous Farming18:23 Remote Intervention and Starlink Integration23:23 Future of Farming Technology24:50 Health and Environmental Benefits25:18 Conclusion and Farewell

Can robots reduce herbicide and fertilizer use on farms by up to 90%?Probably yes.In this episode of TechFirst we chat with Verdant Robotics' CEO Gabe Sibley about SharpShooter, the company's state-of-the-art farm tech that precisely targets herbicide and fertilizer application, massively reducing chemical use.That's huge for the environment.It's also huge for farmer's pocketbooks ... because herbicide and fertilizer are increasingly expensive.We dive into: - How Sharpshooter targets plants with pinpoint accuracy — 240 shots per second - Why this approach can save farmers millions in input costs - The environmental benefits for soil, water, and food - How AI and edge computing make split-second farm decisions possible - The future of robotics in agricultureIf you’re interested in agtech, AI, or sustainable farming, this one’s for you.00:00 Introduction to Robotic Farming00:28 Interview with Gabe Sibley, CEO of Verdant Robotics00:50 How Sharpshooter Technology Works02:40 Economic and Environmental Benefits04:59 Technical Specifications and Capabilities11:11 Future of Agricultural Automation11:54 Personal Insights and Motivation16:39 Conclusion and Final Thoughts

Will your next browser be AI-enabled? AI-first? Perhaps even an AI agent?In this episode of TechFirst, John Koetsier sits down with Henrik Lexow, Senior Product Leader at Opera, to explore Opera Neon, a big step toward agentic browsers that think, act, and create alongside you.(And buy stuff you want, simply hard problems, and do some of your work for you.)Opera’s new browser integrates real AI agents capable of executing multi-step tasks, interacting with web apps, summarizing content, and even building playable games or interactive tools, all inside your browser.We chat about • What an agentic browser is and why it matters • How AI agents like Neon Do and Neon Make automate complex workflows • Opera’s vision for personal, on-device, privacy-aligned AI • Live demos of shopping, summarizing, and game creation using AI • Why your browser might replace your operating system🎮 Watch Henrik demo the Neon agent building a Snake game from scratch🛍️ See AI navigate Amazon, add items to cart, and act independently🧠 Learn why context is king and how this changes everything about search, tabs, and multitasking00:00 Introduction: Should Your Browser Be an AI Agent?00:52 The Evolution of AI in Browsers04:53 Introducing Opera's Agentic Browser11:51 Neon: The Future of Browsing20:26 Exploring the Cart Functionality20:53 Future of AI in Shopping22:39 Trust and Privacy in AI25:05 Neon Make: Generative AI Capabilities26:05 Creating a Snake Game with Neon28:33 Analyzing Car Insurance Policies31:58 Sharing and Publishing with Neon35:53 Conclusion and Future Prospects

Can nuclear waste solve the energy crisis caused by AI data centers? Maybe. And maybe much more, including providing rare elements we need like rhodium, palladium, ruthenium, krypto-85, Americium-241, and more.Amazingly:- 96% of nuclear fuel’s energy is left after it's "used"- Recycling can reduce 10,000-year waste storage needs to just 300 years- Curio’s new process avoids toxic nitric acid and extracts valuable isotopes- 1 recycling plant could meet a third of America’s nuclear fuel needs- Nuclear recycling could enable AI, space travel, and medical breakthroughsIn this episode of TechFirst, host John Koetsier talks with Ed McGinnis, CEO of Curio and former Acting Assistant Secretary for Nuclear Energy at the U.S. Department of Energy. McGinnis is on a mission to revolutionize how we think about nuclear waste, turning it into a powerful resource for energy, rare isotopes, and even precious metals like rhodium.Watch now and subscribe for more deep tech insights.

Neura Robotics officially launched shed 4NE-1 this week. It's the leading European humanoid robot and it's the most powerful humanoid robot in existence right, as far as I'm aware, able to life 100kg or 220 pounds.Neura also released a plan to build 5 million robots by 2030, a new home service robot named MiPA, a new 'Omnisensor' technology platform for integrating input from multiple types of sensors, and an app store for robot skills that anyone can contribute to ... and profit from.In this TechFirst, we chat with David Reger, CEO of Neura Robotics, the leading European humanoid robotics company.We touch on advanced sensors, AI integration, and Neura Robotics' platform that enables extensive customization and scalability. We also chat about significant partnerships with companies like NVIDIA, SAP, and Deutsche Telekom.00:00 Introduction to Humanoid Robotics00:22 Interview with Neura Robotics CEO00:39 Launch of '4NE-1' Humanoid Robot02:26 Technical Specifications and Capabilities04:39 Advanced Sensor Technology09:24 Artificial Skin and Touch Sensory14:05 AI Integration in Robotics15:53 Challenges in Embodied AI17:11 Robot Gyms and Training19:10 Partnerships and Collaborations20:56 The App Store for Robot Skills22:18 AI-Assisted Development Platform29:15 Introducing Mepa: The Home Robot31:41 Future Prospects and Closing Remarks

AI is big these days. Massive. More parameters, more memory, more capability. But what if the future is in tiny AI. Neural networks as small at 8 kilobytes on tiny chips, embedded in everything?Think smart shoes.Smart doors.Smart ... everythingIn this episode of TechFirst, host John Koetsier discusses the future of smart devices with Yubei Chen, co-founder of AIzip. The conversation explores how small-scale AI can revolutionize everyday objects like shoes, cameras, and baby monitors. They delve into how edge AI, which operates at the device level rather than in the cloud, can create efficient, reliable, and cost-effective smart solutions. Chen explains the potential and challenges of integrating AI into traditional devices, including the hardware and software requirements, and touches on the implications for product quality, safety, and cost. This insightful discussion provides a look into the near future of ubiquitous, intelligent technology in our daily lives.00:00 Introduction to Smart Matter01:17 Examples of Smart Applications03:40 Building Efficient AI Models04:01 The Future of Edge AI09:32 Hardware for Smart Devices11:52 Potential Downsides and Challenges18:14 Conclusion and Final Thoughts

IBM has just unveiled its boldest quantum computing roadmap yet: Starling, the first large-scale, fault-tolerant quantum computer—coming in 2029. Capable of running 20,000X more operations than today’s quantum machines, Starling could unlock breakthroughs in chemistry, materials science, and optimization.According to IBM, this is not just a pie-in-the-sky roadmap: they actually have the ability to make Starling happen.In this exclusive conversation, I speak with Jerry Chow, IBM Fellow and Director of Quantum Systems, about the engineering breakthroughs that are making this possible ... especially a radically more efficient error correction code and new multi-layered qubit architectures.We cover:- The shift from millions of physical qubits to manageable logical qubits- Why IBM is using quantum low-density parity check (qLDPC) codes- How modular quantum systems (like Kookaburra and Cockatoo) will scale the technology- Real-world quantum-classical hybrid applications already happening today- Why now is the time for developers to start building quantum-native algorithms00:00 Introduction to the Future of Computing01:04 IBM's Jerry Chow01:49 Quantum Supremacy02:47 IBM's Quantum Roadmap04:03 Technological Innovations in Quantum Computing05:59 Challenges and Solutions in Quantum Computing09:40 Quantum Processor Development14:04 Quantum Computing Applications and Future Prospects20:41 Personal Journey in Quantum Computing24:03 Conclusion and Final Thoughts

How will we scale humanoid robot product to hundreds of thousands and millions of units? In this TechFirst we do a deep dive with Apptronik CEO Jeff Cardenas. We chat about Apptronik's Apollo, his recent $400M+ funding round, the partnership with manufacturing giant Jabil, and much more.We also talk about innovations in AI that have accelerated robot learning and dexterous manipulation, the challenge of scaling manufacturing, and Apptronik's future vision.🎙️ Podcast Summary:Topic: The future of humanoid robotics, funding, manufacturing, and the global AI arms raceGuest: Jeff Cardenas, CEO of Apptronik🦾 Apollo Robot Updates • Apollo 1 debuted in 2023; new versions are coming in 2025 with major upgrades. • Focus areas: larger batteries, swappable parts, improved actuators, and system robustness. • Push toward dexterous manipulation, not just lifting boxes—real industrial work.💰 $403 Million Funding Round • Grew from $350M with new investments from Mercedes, Google (DeepMind), B Capital, Capital Factory, and others. • Mercedes’ legacy of precision and design deeply inspires Cardenas. • Funding will fuel scaling, robustness, and manufacturing partnerships.🏭 Manufacturing Strategy • New partnership with global manufacturing giant Jabil. • Learning from Jabil to avoid premature scaling pitfalls. • Long-term plan includes building out their own capability in Texas and Mexico. • Manufacturing flexibility is key amid tariff and geopolitical uncertainty.🌍 The Global Race: US vs. China • Over 100 humanoid robotics companies worldwide; US and China dominate. • China has invested $138B+ into domestic robotics, outpacing the rest of the world in deployment. • Cardenas calls it the “Space Race of Our Time”, emphasizing urgency and national strategy.📅 Roadmap for Humanoids • 2025: Proving commercial viability in industrial/logistics environments. • 2026+: Volume manufacturing begins for industrial use. • Phase 2: Retail, healthcare, hospitality. • Phase 3 (5+ years): Elder care and home robots — Cardenas’ personal North Star.🧠 Vision & Ethics • “Robots for Humans” isn’t just branding—it’s a human-centered design philosophy. • Deep partnership with Google DeepMind ensures AI is developed responsibly. • Apptronik’s mission: build robots that people want around, not fear.💡 Soundbites • “You don’t just build the robot. You build the machine that builds the machine.” • “We want to be the Apple of robots—designed for people.” • “This is the 1980s of humanoid robots—but innovation is 10x faster.”00:00 Introduction to Humanoid Robot Innovation00:31 Apron's Recent Achievements and Funding01:23 Interview with Apptronik CEO, Jeff Cardenas01:46 Advancements in Apollo Humanoid Robot03:47 Challenges in Scaling Robotics07:56 Future Plans and Human-Centered Robotics10:35 Global Race and Investment in Robotics20:03 Meeting Howard Morgan and B Capital20:41 Inspiration from Mercedes-Benz and Steve Jobs22:02 Global Investors and Supporters23:37 Manufacturing Challenges and Strategies29:36 The Global Race in Humanoid Robotics35:39 Timetable for Humanoid Robots39:57 The Future of Humanoid Robots in Elder Care42:22 Closing Remarks and Final Thoughts

Would you want a personal AI that acts as your twin mind? I've always dreamed of never forgetting anything. And instantly and effortlessly remembering anything I need, right away. Now, an AI-driven app called TwinMind might help me do something similar.In this episode of TechFirst we chat with Daniel George, the CEO of TwinMind. This innovative AI app aims to become your second brain, capturing and processing your life events in real-time. We chat about George's inspiration behind TwinMind, its features, future vision, and the LLM tech making it possible. We also chat about privacy and security concerns.00:00 Introduction to AI and Twin Mind00:51 How Twin Mind Works01:37 Real-World Applications and User Experience03:37 Privacy and Security Concerns11:06 Technology Behind Twin Mind15:17 Future of AI and Twin Mind's Vision21:08 Conclusion and Final Thoughts

Microsoft just announced a massive quantum computer breakthrough that uses an entirely new state of matter. The new quantum computer uses topological superconductors to create stable qubits with low error rates. Topological superconductors enable stable qubits by utilizing Majorana zero modes to protect quantum information from decoherence.The result: Microsoft should have a fault-tolerant usable quantum computer this decade. As in, before 2030.In this TechFirst, we talk with Microsoft's head of quantum hardware, Chetan Nayak, who has been working on solving this problem for literally 19 years, and he talks us through the technology and what it means for quantum computer. He explains the methods to measure this new state non-destructively, the novel architecture that leverages it, and Microsoft's ambitious roadmap towards building a fault-tolerant quantum computer within this decade. The conversation delves into potential future applications, the integration of this technology into global data infrastructures, and the transformative possibilities it holds for various fields, including chemistry, materials science, and beyond.00:00 Introduction to Fault Tolerant Quantum Computing00:48 Understanding the New Phase of Matter: Topological Superconductor02:10 Properties and Applications of Superconductors03:11 Creating and Engineering Topological Superconductors05:16 The Significance of Topological Superconductors for Qubits09:54 Measuring Quantum States with Quantum Dots13:03 Building and Testing Quantum Devices19:43 Future Roadmap for Quantum Processors19:53 Unveiling the Quantum Roadmap20:34 DARPA Collaboration and Engineering Milestones21:23 Fabrication and Demonstration of the Eight Qubit Processor21:43 Accelerating Quantum Progress23:22 Scaling Quantum Computers for Practical Applications27:04 The Long Journey of Quantum Research at Microsoft33:24 Future Prospects and Challenges in Quantum Computing38:10 Quantum Computing's Role in Addressing Global Issues42:32 Reflections on a 19-Year Journey

What humanoid robots is Europe working on? There are maybe 100 humanoid robot companies on the planet, and 16 major ones, but none in Europe according to Peter Diamandis' recent report. That might just have changed.Neura Robotics out of Germany is working on the third generation of its 4NE-1 robot and CEO David Reger says in June they'll be releasing it. And it should be the best humanoid robot on the planet, he says.In this TechFirst we sit down and chat about Europe's answer to humanoid robots, and what Reger sees as a significantly pro-social and pro-human means to bring AI and robotics into the world. We discover how Neuro Robotics is innovating with their upcoming Gen 3 humanoid robot, 4NE-1, learn about their unique approach to robotics, including responsive AI, real-time data streaming, and the development of a sensitive robotic skin. We also explore the future of work, the race against global competitors, and what AI-driven humanoid robots mean for society. 00:00 European Humanoid Robots01:09 The Concept of 'For Anyone' Robots01:46 Rapid Innovation and Development06:29 Challenges in Humanoid Robotics09:02 Neuro Robotics' Unique Approach17:53 Collaborative Market Strategy19:55 Teasing the Third Generation Robot20:10 Challenges in Robot Sensing and Interaction20:50 Innovations in Robot Skin and Sensors22:59 Speed and Agility in Robotics25:38 The Global Race in Robotics28:46 The Future of Humanoid Robots31:45 Balancing Technology and Society34:03 The Role of AI and Robotics in Human Life38:27 Concluding Thoughts and Vision

It feels like we're at a tipping point right now in humanoid robotics. Models are getting released faster and faster, more and more capable than ever. Robots are actually taking paying gigs in warehouses and factories, and there's accelerating innovation. Author, engineer, doctor, investor, and entrepreneur Peter Diamandis just released a major report on the entire industry, and together we dive into what's happening and what's changing. One prediction he made: we'll have humanoid robots in the home, helping us with our work, by 2026 in beta. We discuss recent advancements, like the shipment of new models by Agility Robotics and Figure, and the development of Tesla's Optimus. Peter Diamandis shares insights from his extensive report on the state of humanoid robotics, highlighting key players in both the United States and China. We also talk about the implications of having humanoid robots integrated into various industries, the potential for radically reduced labor costs, and the impact on global economics. And we touch on the broader societal impact, evoking considerations for purpose and struggle in a highly automated future. 00:00 Introduction to Humanoid Robots 01:07 Meet Our Expert Guest: Peter Diamandis 01:33 The Rapid Evolution of Humanoid Robots 03:06 The Future of Humanoid Robots in Society 07:13 Economic Implications of Humanoid Robots 12:17 Technological Advancements and Human Adaptation 19:28 The Design and Functionality of Humanoid Robots 22:00 Future of Work: Robots Taking Over 22:39 The Evolution of Robot Design 23:08 Challenges and Early Days of Robotics 23:42 The Rise of Robot Companies 24:26 Integration of AI and Robotics 25:56 China's Role in the Robotics Revolution 28:58 3D Printing and Robotics 30:22 Top Players in the Robotics Industry 36:31 Robots in Medicine and Surgery 38:43 Conclusion and Upcoming Events