Humanoid Daily

John Koetsier
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Humanoid robot news: all the top stories, updated every single weekday.

  1. 8h ago

    Agility Robotics CEO: $465M, 10,000 robots/year, Digit 5

    Agility Robotics is going public with $465 million in new capital, $300 million in pending robot orders, and a factory capable of producing 10,000 humanoid robots annually. In this exclusive interview, Agility Robotics CEO Peggy Johnson joins John Koetsier to discuss the company's Nasdaq debut, its next-generation Digit 5 humanoid, and what it really takes to scale humanoid robotics. We dig into: - $465 million in capital and $300 million in pending orders - 30+ customers in the pipeline, targeting 100+ by the end of 2027 - Digit 5's ability to work outside safety cages - 90 minutes of work, nine minutes of charging, and 20-hour workdays - 65,000+ hours of real-world robot training data - 50-pound lifting capacity and interchangeable hands - RoboFab's capacity for 10,000 robots per year - Humanoids moving beyond warehouses into manufacturing, retail, and more Johnson also explains why real-world deployment data is critical to robot intelligence, and why Digit 5 is the platform Agility believes it can finally scale. Subscribe for more conversations about AI, humanoid robotics, autonomous systems, and the future of technology. More humanoid robotics news: https://www.humanoidmegahub.com #HumanoidRobots #AgilityRobotics #Digit5 #Robotics #PhysicalAI 00:00 Agility Robotics goes public 01:35 $465M in capital and $300M in orders 03:45 The race for robot training data 05:45 65,000 hours of real-world robot data 07:10 Why Digit 5 is ready to scale 09:35 Digit 5: 20-hour workdays and fast charging 10:50 50-pound payloads and interchangeable hands 12:20 Building 10,000 humanoids a year 13:55 Life as a publicly traded robotics company 15:15 The labor shortage driving robot demand 16:15 Humanoid robots in retail and beyond

  2. 6d ago

    NVIDIA Cosmos vs Saturn ARC: better robot training data, not more?

    Can a robotics world model run at 250 frames per second while NVIDIA's Cosmos runs at roughly 1 FPS? Saturn Dynamics CEO Elisa Seghetti says her company's ARC technology can do exactly that. In this episode, we explore how world models could transform robot training, why high-quality industrial data might outperform massive datasets, and what it will actually take to get humanoid robots working reliably in factories. We discuss: - 250 FPS vs. 1 FPS: Saturn's claimed performance advantage over competing world models - World models vs. simulators: How ARC differs from NVIDIA Cosmos and Isaac Sim - Reinforcement learning: Moving robots from 70–80% success rates toward industrial reliability - Edge AI: Why trillion-parameter models don't make economic sense for robot deployments - Humanoid robots: Why wheeled humanoids and mobile manipulators may make more sense in factories - The robotics supply chain: Why today's vertically integrated robot companies may eventually resemble the automotive industry - Robot training data: Why Saturn is betting on high-quality industrial demonstrations instead of egocentric data Seghetti also shares her predictions for the next 12–18 months, including why the robot data provider market could shrink as better models learn from fewer demonstrations. 00:00 Introduction: the race to train robots 01:00 Meet Saturn Dynamics CEO Elisa Seghetti 01:45 The different approaches to robot training 03:45 Can frontier AI models control robots? 05:20 How world models work 07:30 Making robots easier to train 09:15 Saturn ARC vs. NVIDIA Cosmos and Isaac Sim 11:10 Where humanoid robots fit in 13:45 Are robotics companies wasting money on training? 15:00 Why robotics needs a supply chain 17:20 Vertical integration and robot AI security 19:00 Safety, guardrails, and industrial deployment 21:20 The next 18 months for Saturn Dynamics 22:40 Will the robot data market shrink? 23:40 Closing thoughts #Robotics #HumanoidRobots #PhysicalAI #WorldModels #NVIDIA #RobotLearning

  3. Oct 15

    You can now vibe code a robot: Standard Bots CEO Evan Beard

    What if you could program an industrial robot just by talking to it? That's what Standard Bots is making possible with a new generation of AI-powered robot training tools. In this episode of Humanoid (almost) Daily, I talk with Evan Beard, co-founder and CEO of Standard Bots, about making industrial robots as easy to use as an iPhone ... and why he believes this could help bring about the ChatGPT moment for physical AI. Standard Bots is announcing three new capabilities that dramatically simplify robot deployment and training: - Agent: Vibe code your robot using natural language. Tell it what you want to automate, and AI helps build the program. - Locate: Train computer vision models to recognize and locate objects in seconds, without expensive custom engineering. - Inspect: Working with Roboflow, train AI models to identify defects, scratches, and other quality issues. We also discuss Showpath, a beta capability that allows robots to learn new tasks from just a few demonstrations. Evan explains why traditional industrial automation is so expensive and brittle, why most robots still require specialized engineers to program them, and how AI could make automation accessible to smaller businesses. The bigger vision? Building the Anthropic of the physical world — and making robots intelligent enough to adapt when real-world conditions change. In this conversation: - Why deploying industrial robots traditionally costs so much - How natural-language programming changes robot automation - Training robot vision models in seconds instead of weeks - Teaching robots new tasks through demonstrations - Why flexible AI-powered automation could deliver better ROI - The possibility of a ChatGPT moment for robotics About Standard Bots: https://standardbots.com More humanoid robotics and physical AI news: https://humanoidmegahub.com Subscribe for conversations with the people building the future of robotics, AI, and automation. #robotics #PhysicalAI #ArtificialIntelligence #StandardBots #RobotTraining #Automation #VibeCoding

  4. Oct 13

    The future of humanoid robots isn't JUST human: Haomiao Huang, Matter Venture Partners

    The future of humanoid robots might not look human at all. In fact, the "humanoid robots" of the future could have wheels instead of legs, four arms instead of two, or even look more like spiders than people. That's the provocative argument from Haomiao Huang, founding partner of Matter Venture Partners, which just raised a $450 million fund to invest in robotics, physical AI, semiconductors, and other deep technologies. His perspective: "Humanoid is a state of mind, not a specific type of robot." What matters isn't whether a robot walks on two legs or looks like a person. It's whether that robot can perform multiple tasks, manipulate objects, navigate human environments, and adapt to new situations without being completely reprogrammed. In other words, the real revolution isn't humanoid robots. It's general-purpose robots. In this episode of Humanoid (almost) Daily, we explore why Huang believes we're entering a golden age of robotics, what's still holding the industry back, and what the next generation of robots might look like. We discuss: - Why humanoid robots don't actually need to look human - How general-purpose robots could transform manufacturing, logistics, and eventually our homes - Why today's humanoids resemble the clunky wearable computers of the 1980s - Whether robot manufacturers are scaling before finding product-market fit - Why AI models, compute, and demand are converging to accelerate robotics - The hardware and training-data bottlenecks still holding robots back - Why robots like Dexterity's Mech and Path Robotics' welding systems might represent the near-term future - Where Matter Venture Partners is investing its $450 million - Why the most capable robots of the future might resemble spiders more than humans And we get Huang's predictions for what robotics will look like in five to ten years. 00:00 – The golden age of robotics 00:17 – Meet Haomiao Huang: The $450M physical AI fund 00:55 – If AI eats the world, hardware is its teeth 02:05 – Why physical AI is replacing the metaverse hype 03:49 – Bringing AI agents into the physical world 05:44 – Three forces creating the robotics boom 08:22 – Humanoid is a state of mind, not a robot shape 11:40 – Are humanoids scaling before product-market fit? 12:59 – Why robot reliability still isn't good enough 15:11 – Will we need humanoid-safe products? 16:01 – Hardware, AI, data: What's the biggest bottleneck? 16:39 – Why advanced robotics training data is scarce 17:24 – Today's robots are like early personal computers 20:40 – Why robot makers are building custom hardware 22:19 – Robotics, geopolitics, and military applications 24:07 – Where Matter will invest $450 million 26:24 – Predicting humanoid robots in 2031 27:25 – General-purpose industrial robots will scale first 28:31 – Why the ultimate robot might look like a spider 30:03 – Figure, 1X, and the race toward useful home robots 32:06 – Final thoughts

  5. Oct 6

    1000 robots, 1 factory: Hexagon preps for robot fleets at Schaeffler

    Schaeffler plans to put at least 1,000 of Hexagon's Aeon humanoids to work across its global factory network by 2032. In an industry where most deployments are still counted in single digits, that's a very big number. How is that going to work? How does that change things from pilots with 1 or 10 or 50 robots? How does that change the jobs robots do? What does that change about the jobs humans do? In this long-form episode of Humanoid (almost) Daily, we do a deep dive with Hexagon Robotics president Arnaud Robert. Enjoy! 00:00 What does it take to deploy 1,000 humanoids? 01:31 Why 1,000 robots changes the problem 03:02 Why humanoids need to do multiple jobs 03:55 The race for physical AI training data 04:51 Simulation, synthetic and real-world data 06:20 Hexagon's sim-to-real-to-sim loop 08:10 What robot-generated training data captures 10:21 Pilot vs. production-ready humanoids 12:14 The industrial experience advantage 13:12 The two metrics that really matter 15:39 What Hexagon learned from failure 17:35 The humanoid actuator problem 18:47 Why Aeon uses wheels instead of legs 19:59 Yes, a wheeled humanoid can climb stairs 21:28 What the factory of the future looks like 23:42 Using humanoids to eliminate bottlenecks 25:17 Automation exposes the hidden 3% 26:07 Schaeffler's path to 1,000 humanoids 27:18 Train, deploy, scale

  6. Oct 2

    General Robotics: AI agents for vastly faster robot training

    What if deploying a new robot didn't take weeks or months ... but hours? Ashish Kapoor, founder and CEO of General Robotics and former head of Microsoft's Robotics and Autonomous Systems Group, joins Humanoid Daily to explain why robotics still has a massive research-to-deployment gap. And he shares how AI agents could help close it. General Robotics is building GRID, a unified robotics platform designed to bring together robots, simulation, AI models, training, deployment and engineering tools in one place where AI agents can work across the entire stack. We talk about: • Cutting robot onboarding from a month to as little as 2 hours • Using AI agents to engineer and deploy robotic systems • Why robotics is much harder than agentic software development • Creating custom robot simulators in minutes • Why future enterprise robot fleets will include multiple OEMs and form factors • The three layers of robot training • Why foundation models could reshape the robot-data race • Why post-training may ultimately capture much of the value in robotics Kapoor's big thesis: robotics doesn't just need better AI models. It needs a new engineering architecture that can actually get those models onto real robots in the real world. 00:00 The robotics deployment problem 02:15 Auto Engineering: virtual robot engineers 04:20 Why AI agents are harder in robotics 06:35 What General Robotics built with GRID 09:40 AI-generated robot simulations 11:40 Onboarding almost any robot 14:05 The future of mixed robot fleets 16:15 Where General Robotics fits in the stack 19:10 Why robotics needs a different startup playbook 22:05 The three layers of robot training 25:05 Will foundation models change the robot data race? 28:10 Where the value in robotics will be captured 30:00 Closing thoughts

  7. Oct 1

    New hands for Atlas: fewer fingers, more power

    Boston Dynamics just unveiled new hands for its Atlas humanoid robot: four fingers, 13 degrees of freedom, and no pinky. That's a deliberate choice. 1X, Tesla and Genesis AI are building hands with 20 or more degrees of freedom. Boston Dynamics went the other way, betting on simplicity, strength, ruggedness, and hands that can be accurately simulated for reinforcement learning. The team even taped their pinkies to their ring fingers for a day to decide whether Atlas needed one. In this video I break down what's new, how it compares to other humanoid robot hands, what Boston Dynamics hasn't told us yet, and why simulation might matter more than finger count. Get the full story on HumanoidMegaHub https://www.humanoidmegahub.com/news/boston-dynamics-new-atlas-hands Chapters 0:00 No pinky? 0:12 What's new in the Atlas hand 0:30 How it compares to 1X, Tesla and Genesis AI 0:45 The pinky experiment 1:25 Built to survive impacts 1:55 Why simulation matters 2:25 Built for industrial tools 2:35 What we still don't know

  8. Sep 26

    Humanoids + humans: Agility Robotics CEO on new Digit 5

    Agility Robotics is launching Digit 5, its newest humanoid robot. Digit 5 is designed to work in close proximity with humans without the physical safety barriers that have traditionally separated robots from workers. In this episode of Humanoid Daily, we chat with Agility Robotics CEO Peggy Johnson. She explains what has changed with Digit 5, including a 50-pound payload capacity, faster charging, improved vision and human detection, swappable end effectors, and the ability to move between multiple tasks inside logistics and manufacturing facilities. We also dig into one of the biggest challenges facing humanoid robotics: safety. Peggy explains how Agility is working with ANSI and ISO standards, how Digit detects and reacts to nearby humans, and why removing safety cages could unlock much broader deployment of humanoid robots. We discuss where humanoids fit alongside traditional automation and autonomous mobile robots, why Agility chose legs instead of wheels, what the company has learned from more than 65,000 hours of real-world robot operation, and how customers including major logistics and manufacturing companies are helping shape Digit’s development. Peggy also shares how Agility trains new robotic skills using a combination of real-world operational data, simulation tools such as NVIDIA Isaac Sim, and learning from demonstration. Plus, we talk about the increasingly competitive humanoid robotics market, Agility Robotics’ U.S.-based manufacturing strategy, RoboFab, and what Digit 5 could be capable of a year from now compared with day one. Topics include: • Digit 5 and human-robot collaboration• Humanoid robot safety• 50-pound payload capacity• Fast charging and multi-shift operation• Robotics standards and regulation• Legs versus wheels• Warehouse and manufacturing automation• Agility Robotics’ RoboFab• Physical AI and robot training• NVIDIA Isaac Sim• Learning from demonstration• The growing humanoid robotics market 00:00 Digit 5 can now work around humans 00:32 Introducing Agility Robotics’ Digit 5 01:17 50-pound payloads and longer operating time 02:03 Fast charging vs. swappable batteries 03:02 Why Digit can move differently than humans 04:03 The growing industrial labor gap 05:01 Breaking the humanoid safety barrier 05:41 How Digit detects nearby humans 06:18 Building safety standards for humanoid robots 07:05 When Digit 5 will begin deploying 07:30 How fast should a humanoid robot walk? 08:02 What happens when a human gets too close? 09:04 Why Agility is taking a cautious approach 10:03 Swappable grippers and robotic end effectors 11:05 Using the existing robotics ecosystem 11:42 Where humanoid robotics is today 13:00 Moving from one task to end-to-end workflows 14:17 The factory of the future 15:30 Humanoids vs. wheeled robots 16:41 Why legs make sense for Digit 17:36 Connecting Digit with other automation 18:03 The exploding humanoid robotics market 18:42 Agility’s real-world advantage 19:17 What Agility has learned from customers 20:28 How U.S. policy affects Agility Robotics 21:05 RoboFab and Agility’s U.S. operations 22:04 Expanding Digit 5 into Europe 23:00 How Digit 5 will gain new skills 23:39 The race to train humanoid robots 24:31 Real data, simulation and Isaac Sim 25:02 Learning from demonstration 25:48 Final thoughts

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Humanoid robot news: all the top stories, updated every single weekday.

Information

  • Creator
    John Koetsier
  • Years Active
    2026
  • Episodes
    29
  • Rating
    Clean
  • Copyright
    © John Koetsier
  • Show Website
    Humanoid Daily

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