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Welcome HMND 01 Alpha Bipedal — autonomous, adaptive, built for real-world impact. Made in 5 months, walking in 48 hours. It will power R&D, POCs, safety validation, and AI development. 179 cm | 29 DOFs excluding end-effectors | 15 kg bimanual payload | 12-DOF hands or parallel grippers |... show more

Humanoid

6,055 subscribers

51,542 views • 10 months ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

9 Comments

Mauricio | XMAQUINA10 months ago

👀 @xmaquina

Tyler e/acc10 months ago

Cooking at incredible speeds! Great advancements.

岡田泰彦｜光邦｜AI×印刷エヴァンジェリスト10 months ago

The pace of progress here is wild — 5 months to build and this level of performance already. You’re clearly reshaping what “rapid robotics development” means. 5ヶ月でこの完成度は衝撃です。“ロボティクス開発のスピード感”の定義を塗り替えてますよ。

Dror David Ifrah10 months ago

Damn impressive for 5 months!

Kiitan10 months ago

Looks sick asf! 🔥

The Alloy Mind10 months ago

congrats, impressive work can't wait to see it in real world action !

Saïd Aitmbarek10 months ago

wow, impressive!

Cormac10 months ago

pretty cool but will probably get regulated to death

DigitalEdward.hc10 months ago

Built it on Holochain 👀

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Meet HMND 01 Alpha — UK’s first humanoid robot for industrial use. Built in just 7 months, it’s the fastest-developed humanoid in history. 220 cm | 7.2 km/h | 15 kg payload | 29 active DOF, excluding end-effectors | AI-driven end-to-end reasoning The journey has just begun. The humanoid future is closer than ever. Stay tuned for our Behind the Scenes documentary later today!

Meet HMND 01 Alpha — UK’s first humanoid robot for industrial use. Built in just 7 months, it’s the fastest-developed humanoid in history. 220 cm | 7.2 km/h | 15 kg payload | 29 active DOF, excluding end-effectors | AI-driven end-to-end reasoning The journey has just begun. The humanoid future is closer than ever. Stay tuned for our Behind the Scenes documentary later today!

Humanoid

32,564 views • 1 year ago

NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA. Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory." Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation. NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy: "With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

NEWS: NVIDIA just announced Alpamayo, what CEO Jensen Huang calls the world’s first thinking, reasoning autonomous vehicle AI, launching on U.S. roads later this year, starting with the Mercedes CLA. Jensen: "It's trained end-to-end. Literally from camera in to actuation out; It reasons what action it is about to take, the reason by which is came about that action, and the trajectory." Alpamayo introduces Vision-Language-Action (VLA) models, which enable self-driving systems to interpret what they see, reason about complex driving scenarios, and generate driving actions. The platform includes large reasoning models, simulation tools for testing rare and edge-case scenarios, and open datasets for training and validation. NVIDIA says the approach improves transparency, safety, and robustness in autonomous systems, particularly in complex real-world environments, and supports progress toward higher levels of vehicle autonomy: "With a 10-billion-parameter architecture, Alpamayo 1 uses video input to generate trajectories alongside reasoning traces, showing the logic behind each decision. Developers can adapt Alpamayo 1 into smaller runtime models for vehicle development, or use it as a foundation for AV development tools such as reasoning-based evaluators and auto-labeling systems. Alpamayo 1 provides open model weights and open-source inferencing scripts. Future models in the family will feature larger parameter counts, more detailed reasoning capabilities, more input and output flexibility, and options for commercial usage."

Sawyer Merritt

1,605,090 views • 9 months ago

🤖 The first 3-on-3 humanoid robot football match just took place in Beijing It was the final of China's RoBoLeague, featuring robots from top universities — including Tsinghua. The bots relied entirely on their own algorithms to decide where to run, how to dodge opponents, and when to strike the ball. Each player used cameras and sensors to detect the ball, field, and rivals — making real-time decisions with zero human input. ⚽️ Dressed in black and purple jerseys, the mechanical footballers clumsily ran, fell, got back up — and kept fighting until the end. The match ended with a 5:3 win for team Volcano.

🤖 The first 3-on-3 humanoid robot football match just took place in Beijing It was the final of China's RoBoLeague, featuring robots from top universities — including Tsinghua. The bots relied entirely on their own algorithms to decide where to run, how to dodge opponents, and when to strike the ball. Each player used cameras and sensors to detect the ball, field, and rivals — making real-time decisions with zero human input. ⚽️ Dressed in black and purple jerseys, the mechanical footballers clumsily ran, fell, got back up — and kept fighting until the end. The match ended with a 5:3 win for team Volcano.

NEXTA

71,690 views • 1 year ago

In this episode, OpenAI Chief Research Officer Mark Chen joins allen to flambé shrimp, cook Korean stew, and chat about being at the frontier of AI research: why scaling laws and pre-training still matter, how OpenAI chooses research bets and allocates compute, what it means to develop research taste, why evals are in crisis, how to avoid benchmark-maxing, and what it will take for models to handle long-horizon real-world work, multimodal reasoning, and eventually end-to-end AI research. Timestamps: 0:00 Intro 0:28 The Soup Story 1:52 From Trading to AI Research 3:21 How to Develop Research Taste 5:23 RL, Evals, and Superhuman Benchmarks 8:17 Cooking Begins on the Impulse Stove 8:53 Scaling Laws, Pre-Training, and Reasoning 12:33 OpenAI’s Research Roadmap and Compute Allocation 15:48 What Makes a Great Researcher 19:33 The Evals Crisis and Benchmark-Maxing 24:34 Jagged Intelligence, Context, and Long-Horizon Learning 27:14 Shrimp Flambé and New Research Bets 31:32 Multimodal Models and One Architecture 32:36 Vibe Researching and End-to-End AI Research 34:36 Failed Bets, Postmortems, and OpenAI’s Alpha 37:07 Final Taste Test 37:53 Overrated vs. Underrated AI Research 41:00 Closing

In this episode, OpenAI Chief Research Officer Mark Chen joins allen to flambé shrimp, cook Korean stew, and chat about being at the frontier of AI research: why scaling laws and pre-training still matter, how OpenAI chooses research bets and allocates compute, what it means to develop research taste, why evals are in crisis, how to avoid benchmark-maxing, and what it will take for models to handle long-horizon real-world work, multimodal reasoning, and eventually end-to-end AI research. Timestamps: 0:00 Intro 0:28 The Soup Story 1:52 From Trading to AI Research 3:21 How to Develop Research Taste 5:23 RL, Evals, and Superhuman Benchmarks 8:17 Cooking Begins on the Impulse Stove 8:53 Scaling Laws, Pre-Training, and Reasoning 12:33 OpenAI’s Research Roadmap and Compute Allocation 15:48 What Makes a Great Researcher 19:33 The Evals Crisis and Benchmark-Maxing 24:34 Jagged Intelligence, Context, and Long-Horizon Learning 27:14 Shrimp Flambé and New Research Bets 31:32 Multimodal Models and One Architecture 32:36 Vibe Researching and End-to-End AI Research 34:36 Failed Bets, Postmortems, and OpenAI’s Alpha 37:07 Final Taste Test 37:53 Overrated vs. Underrated AI Research 41:00 Closing

Latent.Space

62,796 views • 3 months ago

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

17,092 views • 4 months ago

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Sprytix

57,512 views • 4 months ago

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Creditcoin 🐧

12,948 views • 3 years ago

U.S. based humanoid robotics company 1X has just unveiled their new tendon-driven robot hands with 25 degrees of freedom (DOF). • Made in USA • Tendon Drive Ratio: 5:1–15:1 • Wrist Dexterity: 3 DOF • Backdrivability: Fully backdrivable • Tactile Sensing: Pressure + location + slip • Finger Force: Up to 45 N • Wrist Torque: 17.75 Nm • Position Accuracy: ±0.2 mm • Waterproof Rating: IP68 • Reliability: >2 million cycles "These hands are designed to do something fundamental: remove the hardware ceiling on what humanoid robots can actually do, and make data the only barrier to capabilities. By matching or surpassing human hands across the dimensions that matter, they ensure our AI models are no longer limited by dexterity. NEO can now perform virtually any task a human can do with their hands– with the precision, adaptability, and gentleness required for real-world environments."

U.S. based humanoid robotics company 1X has just unveiled their new tendon-driven robot hands with 25 degrees of freedom (DOF). • Made in USA • Tendon Drive Ratio: 5:1–15:1 • Wrist Dexterity: 3 DOF • Backdrivability: Fully backdrivable • Tactile Sensing: Pressure + location + slip • Finger Force: Up to 45 N • Wrist Torque: 17.75 Nm • Position Accuracy: ±0.2 mm • Waterproof Rating: IP68 • Reliability: >2 million cycles "These hands are designed to do something fundamental: remove the hardware ceiling on what humanoid robots can actually do, and make data the only barrier to capabilities. By matching or surpassing human hands across the dimensions that matter, they ensure our AI models are no longer limited by dexterity. NEO can now perform virtually any task a human can do with their hands– with the precision, adaptability, and gentleness required for real-world environments."

Sawyer Merritt

744,955 views • 2 months ago

$CLIENT INTERVIEW: $3B REAL ESTATE ON-CHAIN—THE FUTURE OF RWAs? Sponsored by MultiBank. From luxury towers to tokenized rent yields and daily income on $50 investments, mb.io, Mavryk Network, and MAG Global just dropped the biggest RWA deal in crypto history—live at Token2049 Dubai. In this power-packed roundtable, CEO Zak, CFO Amer Jabr, and founder Alex Davis reveal how they’re fractionalizing iconic Dubai real estate—including the Ritz-Carlton Keturah Residences—and what it means for retail and institutional investors alike. Multibank also shows how self-custody, real-time yield and an ecosystem powered by the $MBG token redefine access to the world’s largest asset class. 00:55 – The $3B deal revealed: RWA tokenization goes mainstream. 01:28 – What are users buying? A breakdown of the real estate portfolio: ready, off-plan, residential, and commercial. 01:56 – Dubai’s Ritz-Carlton Keturah Residence is the flagship listing. 02:48 – What is Mavryk Network? A Layer 1 purpose-built for secure RWA DeFi. 03:49 – MAG’s $15B city-scale project: 20M sq. ft. of high-end assets. 04:56 – From $50 minimums to daily yields: How MultiBank opens real estate to everyone. 06:56 – Tokenization = accessibility + liquidity: solving real estate’s biggest pain points. 08:02 – Why fractionalizing real estate could unlock $380T in global value. 09:14 – Secondary market access and trading—real-time exit strategies enabled. 09:58 – Borrowing with tokenized assets: non-custodial, credit-free mortgages explained. 11:12 – Why on-chain wins: self-custody, transparency, and ecosystem integration. 14:38 – How MultiBank bridges TradFi and DeFi—without overwhelming users. 15:52 – Why past models failed (REITs, timeshares)—and this one won’t. 15:59 – Inside the $MBG token: powering perks, access, and ecosystem incentives. 19:14 – Final thoughts: Why this RWA launch is a “no-brainer” and what’s next. Disclaimer: This is a paid sponsorship. It is not financial or investment advice. Cryptocurrency—especially memecoins—can be extremely risky and unpredictable, so do your own research and be prepared to lose any money you invest.$

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Mario Nawfal

252,728 views • 1 year ago

There was a time I built a business transporting dogs for money. At the end of every trip, I’d take what I made and turn it all into Dogecoin. By the time I got back east, I’d have more Doge, but less USD. More belief, less certainty. I did it again and again. Call it stubbornness, faith, or just being a glutton for punishment. But it wasn’t until I rewatched one video…over and over, that it finally hit me. The goods are the dogs I save. The service is delivering them to homes that will love them. That’s when I stopped charging. Stopped chasing. And started serving. Because real value isn’t measured in money. It’s measured in lives changed, theirs and mine.

There was a time I built a business transporting dogs for money. At the end of every trip, I’d take what I made and turn it all into Dogecoin. By the time I got back east, I’d have more Doge, but less USD. More belief, less certainty. I did it again and again. Call it stubbornness, faith, or just being a glutton for punishment. But it wasn’t until I rewatched one video…over and over, that it finally hit me. The goods are the dogs I save. The service is delivering them to homes that will love them. That’s when I stopped charging. Stopped chasing. And started serving. Because real value isn’t measured in money. It’s measured in lives changed, theirs and mine.

Doge Van

30,990 views • 11 months ago

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Lavender 💜

14,397 views • 1 year ago

how to build, launch and grow your startup: complete basics that every founder learns by accident 00:00 Intro to building 00:14 The build-measure-learn loop 04:12 What makes a good one-liner 05:40 Rewriting bad one-liners 08:43 Billboards: the Monaco trick 10:12 Set a specific 5-week goal 13:43 Goals that never end will break you 15:42 Intro to Content 18:15 Why luck is the real product 25:03 Fix your bio right now 28:24 Cheat sheet for viral launches 30:49 Step 1: Find 10 strangers (not founders) 33:07 Step 2: The "oh, that makes sense" moment 34:26 Step 3: A visually clear use case 42:29 The $100 launch video that hit 4M 46:04 Context in the first 2 seconds 48:15 Writing with an eraser 51:11 Framework 1: Comparison 54:29 Framework 2: Antagonist 56:01 Framework 3: The Gap 59:37 Be the world's leading expert 01:06:42 Steal your customer's FYP 01:11:47 The 25-video spreadsheet 01:19:36 Intro to Growth 01:21:32 The only metric that matters 01:23:20 Why 1M LP hits is bad growth 01:26:53 The #1 rule on user calls 01:27:15 The AI realtor story 01:34:19 Why Reddit beats Twitter 01:40:15 The landing page that turns pink

how to build, launch and grow your startup: complete basics that every founder learns by accident 00:00 Intro to building 00:14 The build-measure-learn loop 04:12 What makes a good one-liner 05:40 Rewriting bad one-liners 08:43 Billboards: the Monaco trick 10:12 Set a specific 5-week goal 13:43 Goals that never end will break you 15:42 Intro to Content 18:15 Why luck is the real product 25:03 Fix your bio right now 28:24 Cheat sheet for viral launches 30:49 Step 1: Find 10 strangers (not founders) 33:07 Step 2: The "oh, that makes sense" moment 34:26 Step 3: A visually clear use case 42:29 The $100 launch video that hit 4M 46:04 Context in the first 2 seconds 48:15 Writing with an eraser 51:11 Framework 1: Comparison 54:29 Framework 2: Antagonist 56:01 Framework 3: The Gap 59:37 Be the world's leading expert 01:06:42 Steal your customer's FYP 01:11:47 The 25-video spreadsheet 01:19:36 Intro to Growth 01:21:32 The only metric that matters 01:23:20 Why 1M LP hits is bad growth 01:26:53 The #1 rule on user calls 01:27:15 The AI realtor story 01:34:19 Why Reddit beats Twitter 01:40:15 The landing page that turns pink

Founders Inc

21,257 views • 5 months ago

TARS has made some big announcements at ICRA 2026. DexHand - A dexterous hand with 1:1 replication of human metacarpal and finger structure, multi-axis thumb opposition - Quasi-direct-drive + backdrivable joints, 21 degrees of freedom - All 26 ASL letter signs reproduced at high precision -0.05mm fingertip tactile sensing - Data. Model. Hand. Fused into one embodied AI-native dexterous hand. OmniVTA with TacForeSight A visuo-tactile world model for general-use, paired with TacForeSight, a force-guided technology that not only allows robots to understand contact but also enables them to predict contact before it happens. - Semantic touch ("slippery," "rough," "soft," "hard") enabling texture-based material cognition. - Operates inside a real-time closed loop - Contact state prediction and reaction at the microsecond scale, faster than human AWE 3.0 - Claimed to be the world's leading general-purpose embodied foundation model for real-world work - A1 robot packing demo as the showcase: long-horizon, bimanual, with autonomous error recovery and end-to-end imitation learning - Set a Guinness World Record in March 2026 for "Most sub-millimeter wire harness assembled by a robot in one hour" - SenseHub data acquisition suite captures human experience data to train AWE 3.0

TARS has made some big announcements at ICRA 2026. DexHand - A dexterous hand with 1:1 replication of human metacarpal and finger structure, multi-axis thumb opposition - Quasi-direct-drive + backdrivable joints, 21 degrees of freedom - All 26 ASL letter signs reproduced at high precision -0.05mm fingertip tactile sensing - Data. Model. Hand. Fused into one embodied AI-native dexterous hand. OmniVTA with TacForeSight A visuo-tactile world model for general-use, paired with TacForeSight, a force-guided technology that not only allows robots to understand contact but also enables them to predict contact before it happens. - Semantic touch ("slippery," "rough," "soft," "hard") enabling texture-based material cognition. - Operates inside a real-time closed loop - Contact state prediction and reaction at the microsecond scale, faster than human AWE 3.0 - Claimed to be the world's leading general-purpose embodied foundation model for real-world work - A1 robot packing demo as the showcase: long-horizon, bimanual, with autonomous error recovery and end-to-end imitation learning - Set a Guinness World Record in March 2026 for "Most sub-millimeter wire harness assembled by a robot in one hour" - SenseHub data acquisition suite captures human experience data to train AWE 3.0

The Humanoid Hub

11,322 views • 3 months ago

𝗖𝗵𝗶𝗻𝗮 𝗶𝘀 𝗳𝗶𝗻𝗶𝘀𝗵𝗶𝗻𝗴 𝘁𝗵𝗲 𝗵𝘂𝗺𝗮𝗻𝗼𝗶𝗱 𝗿𝗼𝗯𝗼𝘁 𝗿𝗮𝗰𝗲 𝗯𝗲𝗳𝗼𝗿𝗲 𝗺𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝘀𝘁 𝗿𝗲𝗮𝗹𝗶𝘇𝗲𝘀 𝗶𝘁 𝗵𝗮𝘀 𝘀𝘁𝗮𝗿𝘁𝗲𝗱. AGIBOT held its Partner Conference in Shanghai last week. The real headline wasn't the new hardware. It was their CTO standing on stage, telling investors that humanoid R&D season is over. 2026, he said, is "Deployment Year One." Not research. Not demos. Deployment into real factories, real warehouses, real stores. The manufacturing ramp is getting faster. 1,000 humanoid robots in the first 2 years. Another 4,000 in the next 12 months. Another 5,000 in just 3 months after that. AGIBOT is now shipping more humanoids per quarter than most US robotics companies have built in their entire existence. Then came the announcements the industry will spend the rest of the year reacting to. AIMA. The first full-stack open architecture for embodied AI. A unified robot operating system called Link-U, three dev platforms for motion, interaction, and task creation, plus an open agent framework. Any developer can build on top of it. This is the Android play for humanoids. GO-2. A vision-language-action foundation model with Action Chain-of-Thought reasoning. Planning and execution collapsed into one model. GE-2. A world model for simulation, strategy testing, and sim-to-real transfer. AGIBOT WORLD 2026. An open-source, production-grade real-world dataset pulled from actual industrial, logistics, hotel, and commercial sites. Seven standardized "productivity packages" covering logistics sorting, retail service, security patrol, commercial cleaning, and more. Plug, deploy, bill. A 5-year, $280 million commitment to seed a global developer and partner ecosystem. Now look at the competition. Boston Dynamics has been building humanoids since 1992. Tesla's Optimus is still climbing its own hype curve. Apptronik and Agility are well-funded but pre-scale on real deployments. AGIBOT has pulled all of this off in three years, with no acquisitions, no legacy platform, and no IPO distractions. While the West is still asking when humanoids will scale, China is already shipping them by the thousand.

𝗖𝗵𝗶𝗻𝗮 𝗶𝘀 𝗳𝗶𝗻𝗶𝘀𝗵𝗶𝗻𝗴 𝘁𝗵𝗲 𝗵𝘂𝗺𝗮𝗻𝗼𝗶𝗱 𝗿𝗼𝗯𝗼𝘁 𝗿𝗮𝗰𝗲 𝗯𝗲𝗳𝗼𝗿𝗲 𝗺𝗼𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝘀𝘁 𝗿𝗲𝗮𝗹𝗶𝘇𝗲𝘀 𝗶𝘁 𝗵𝗮𝘀 𝘀𝘁𝗮𝗿𝘁𝗲𝗱. AGIBOT held its Partner Conference in Shanghai last week. The real headline wasn't the new hardware. It was their CTO standing on stage, telling investors that humanoid R&D season is over. 2026, he said, is "Deployment Year One." Not research. Not demos. Deployment into real factories, real warehouses, real stores. The manufacturing ramp is getting faster. 1,000 humanoid robots in the first 2 years. Another 4,000 in the next 12 months. Another 5,000 in just 3 months after that. AGIBOT is now shipping more humanoids per quarter than most US robotics companies have built in their entire existence. Then came the announcements the industry will spend the rest of the year reacting to. AIMA. The first full-stack open architecture for embodied AI. A unified robot operating system called Link-U, three dev platforms for motion, interaction, and task creation, plus an open agent framework. Any developer can build on top of it. This is the Android play for humanoids. GO-2. A vision-language-action foundation model with Action Chain-of-Thought reasoning. Planning and execution collapsed into one model. GE-2. A world model for simulation, strategy testing, and sim-to-real transfer. AGIBOT WORLD 2026. An open-source, production-grade real-world dataset pulled from actual industrial, logistics, hotel, and commercial sites. Seven standardized "productivity packages" covering logistics sorting, retail service, security patrol, commercial cleaning, and more. Plug, deploy, bill. A 5-year, $280 million commitment to seed a global developer and partner ecosystem. Now look at the competition. Boston Dynamics has been building humanoids since 1992. Tesla's Optimus is still climbing its own hype curve. Apptronik and Agility are well-funded but pre-scale on real deployments. AGIBOT has pulled all of this off in three years, with no acquisitions, no legacy platform, and no IPO distractions. While the West is still asking when humanoids will scale, China is already shipping them by the thousand.

Shruti

214,939 views • 5 months ago

A stunning piece of engineering!! 1X unveils the new humanoid hand for NEO - 25 degrees of freedom: 22 fully actuated in the fingers and palm, plus 3 at the wrist. - The DoF are distributed anatomically rather than evenly, deliberately biased toward a thumb that genuinely opposes the fingers. - In-house tendon-driven, quasi-direct-drive running low gear ratios of ~5:1 to 15:1 vs the typical 100:1–200:1. - Motors live in the forearm and pull tendons through the wrist. This keeps the hand light and its inertia low while producing high forces. Sensing - All 25 DoF are natively force-controlled and fully backdrivable. Every joint doubles as a force sensor. - Very important, closed-loop proprioception: it always knows its own pose and effort without looking. - Tactile skin across the fingertips and surfaces measuring contact and shear. This helps with adaptive gripping in real time. Safety and durability - IP68 waterproof and food-safe, so it can wash its own hands. - Compliant by construction: the low gear ratios, tendon drive, and low distal inertia let external impacts safely backdrive the fingers. It yields when hit by a hammer or caught in a drawer. - Full finger assemblies validated to millions of cycles. Manufacturing - Deep vertical integration: in-house motors, custom electronics, and tendon systems. - Hundreds built already, with capacity to produce 10,000 hands this year. "An API to the Physical World"

A stunning piece of engineering!! 1X unveils the new humanoid hand for NEO - 25 degrees of freedom: 22 fully actuated in the fingers and palm, plus 3 at the wrist. - The DoF are distributed anatomically rather than evenly, deliberately biased toward a thumb that genuinely opposes the fingers. - In-house tendon-driven, quasi-direct-drive running low gear ratios of ~5:1 to 15:1 vs the typical 100:1–200:1. - Motors live in the forearm and pull tendons through the wrist. This keeps the hand light and its inertia low while producing high forces. Sensing - All 25 DoF are natively force-controlled and fully backdrivable. Every joint doubles as a force sensor. - Very important, closed-loop proprioception: it always knows its own pose and effort without looking. - Tactile skin across the fingertips and surfaces measuring contact and shear. This helps with adaptive gripping in real time. Safety and durability - IP68 waterproof and food-safe, so it can wash its own hands. - Compliant by construction: the low gear ratios, tendon drive, and low distal inertia let external impacts safely backdrive the fingers. It yields when hit by a hammer or caught in a drawer. - Full finger assemblies validated to millions of cycles. Manufacturing - Deep vertical integration: in-house motors, custom electronics, and tendon systems. - Hundreds built already, with capacity to produce 10,000 hands this year. "An API to the Physical World"

The Humanoid Hub

1,277,943 views • 2 months ago

ASIMO: Honda’s Trailblazing Humanoid Robot Gone but not forgotten. — ASIMO, or Advanced Step in Innovative Mobility is a landmark achievement in robotics, unveiled by Honda Motor Co., Ltd. on October 31, 2000. Born from nearly two decades of research starting in 1986, ASIMO was designed to navigate human environments and assist with daily tasks. Standing at 4 feet 3 inches and weighing 110 pounds was a sleek, astronaut-like design made it approachable and futuristic. ASIMO’s advanced capabilities, including bipedal walking, object manipulation, and voice recognition, showcased Honda’s expertise in robotics, AI, and sensor technology, positioning it as a global symbol of innovation. ASIMO’s standout features included its lIntelligent Real-Time Flexible Walking (i-WALK) system, enabling it to climb stairs, run at 5.6 mph, and adapt to uneven surfaces. Equipped with cameras, ultrasonic sensors, and dexterous hands, it could avoid obstacles, pour drinks, and recognize gestures, demonstrating remarkable human-robot interaction. Over the years, upgrades enhanced its autonomy, hand dexterity, and even sign language capabilities, with the final 2014 model able to jump and balance on one leg. While not fully autonomous, ASIMO’s real-time decision-making and 40-minute battery life marked significant strides in humanoid robotics. Though ASIMO never became a commercial product, its impact was profound, inspiring STEM education and future robotic innovations. It appeared at global expos, conducted orchestras, Retired in 2018, ASIMO’s legacy lives on, having influenced projects like Boston Dynamics’ Atlas and contributed to Honda’s mobility devices. Honda should bring Asimo back. Some of the technology is more tangible recent today. This video is 25 years old…

ASIMO: Honda’s Trailblazing Humanoid Robot Gone but not forgotten. — ASIMO, or Advanced Step in Innovative Mobility is a landmark achievement in robotics, unveiled by Honda Motor Co., Ltd. on October 31, 2000. Born from nearly two decades of research starting in 1986, ASIMO was designed to navigate human environments and assist with daily tasks. Standing at 4 feet 3 inches and weighing 110 pounds was a sleek, astronaut-like design made it approachable and futuristic. ASIMO’s advanced capabilities, including bipedal walking, object manipulation, and voice recognition, showcased Honda’s expertise in robotics, AI, and sensor technology, positioning it as a global symbol of innovation. ASIMO’s standout features included its lIntelligent Real-Time Flexible Walking (i-WALK) system, enabling it to climb stairs, run at 5.6 mph, and adapt to uneven surfaces. Equipped with cameras, ultrasonic sensors, and dexterous hands, it could avoid obstacles, pour drinks, and recognize gestures, demonstrating remarkable human-robot interaction. Over the years, upgrades enhanced its autonomy, hand dexterity, and even sign language capabilities, with the final 2014 model able to jump and balance on one leg. While not fully autonomous, ASIMO’s real-time decision-making and 40-minute battery life marked significant strides in humanoid robotics. Though ASIMO never became a commercial product, its impact was profound, inspiring STEM education and future robotic innovations. It appeared at global expos, conducted orchestras, Retired in 2018, ASIMO’s legacy lives on, having influenced projects like Boston Dynamics’ Atlas and contributed to Honda’s mobility devices. Honda should bring Asimo back. Some of the technology is more tangible recent today. This video is 25 years old…

Brian Roemmele

16,862 views • 1 year ago