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Teaching robots how to paint! 💅🏼 This painting robot, for example, mimics human movements with precision to handle repetitive, and tiring tasks. A special device memorizes points in 3D space, which are then sent to the robot's control. The result? A robot that, after a single demonstration, can perform... show more

Lukas Ziegler

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38,319 次观看 • 1 年前 •via X (Twitter)

教育艺术科学技术

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Pi Ventures-Backed OpenMind Opens Waitlist For Humanoid Robot Control Pi Network (Pi Network) Ventures backed OpenMind (OpenMind) has opened the waitlist for Instabody, a platform that lets users remotely control a real humanoid robot. The company said users can see the world through the robot's eyes and directly control its movements. It believes giving people the controls will help shape how robots evolve. OpenMind previously launched a robot app store built on its OM1 operating system, allowing developers to add new skills to humanoid and quadruped robots.

Pi Ventures-Backed OpenMind Opens Waitlist For Humanoid Robot Control Pi Network (Pi Network) Ventures backed OpenMind (OpenMind) has opened the waitlist for Instabody, a platform that lets users remotely control a real humanoid robot. The company said users can see the world through the robot's eyes and directly control its movements. It believes giving people the controls will help shape how robots evolve. OpenMind previously launched a robot app store built on its OM1 operating system, allowing developers to add new skills to humanoid and quadruped robots.

BSCN

55,889 次观看 • 27 天前

Physical AI won't just be limited to controlling robots and spatial computing; it will usher in a new era of machine design. You will be able to "vibe design" a robot - or a part of a robot - or a machine that manufactures robot parts - using high-level specifications such as preferred architecture, material constraints, cost constraints, supply chain and geographic limitations and scalability. AI will provide preliminary designs that human experts can tweak and tune, corresponding supplier catalogs, and machining options. It will also project the talent and CAPEX required at various phases of hardware development.

Physical AI won't just be limited to controlling robots and spatial computing; it will usher in a new era of machine design. You will be able to "vibe design" a robot - or a part of a robot - or a machine that manufactures robot parts - using high-level specifications such as preferred architecture, material constraints, cost constraints, supply chain and geographic limitations and scalability. AI will provide preliminary designs that human experts can tweak and tune, corresponding supplier catalogs, and machining options. It will also project the talent and CAPEX required at various phases of hardware development.

The Humanoid Hub

48,715 次观看 • 6 个月前

⚠️ THIS ROBOT ANSWERED A HOSTILE QUESTION IN 9 WORDS. THAT'S THE SPEC SHEET NOBODY IS READING. "To make humans lives easier and a little more interesting." That answer wasn't charming. It was precise. Break it down: → Addresses utility (easier) → Addresses engagement (more interesting) → Centers the human, not the robot → Delivered in under 10 words to a hostile prompt That is a mission statement that survives contact with a skeptic. In public. Unrehearsed. Procurement teams building out human-robot workflows don't need the robot to be impressive. They need it to be explainable, to workers, to floor managers, to anyone who stops it and asks why it exists. This robot just passed that test. Nobody runs that number on a demo reel. This one ran it live.

⚠️ THIS ROBOT ANSWERED A HOSTILE QUESTION IN 9 WORDS. THAT'S THE SPEC SHEET NOBODY IS READING. "To make humans lives easier and a little more interesting." That answer wasn't charming. It was precise. Break it down: → Addresses utility (easier) → Addresses engagement (more interesting) → Centers the human, not the robot → Delivered in under 10 words to a hostile prompt That is a mission statement that survives contact with a skeptic. In public. Unrehearsed. Procurement teams building out human-robot workflows don't need the robot to be impressive. They need it to be explainable, to workers, to floor managers, to anyone who stops it and asks why it exists. This robot just passed that test. Nobody runs that number on a demo reel. This one ran it live.

Shredder

202,894 次观看 • 10 天前

Elon Musk today on Optimus robot: "You’ve probably seen a lot of impressive demos of robots on the internet, but those demonstrations are pre-programmed or remote-controlled. There is no humanoid robot that can actually do generalized tasks. Optimus will be the first one that will be capable of doing that, in just a demo, it’s generally useful in day-to-day life."

Elon Musk today on Optimus robot: "You’ve probably seen a lot of impressive demos of robots on the internet, but those demonstrations are pre-programmed or remote-controlled. There is no humanoid robot that can actually do generalized tasks. Optimus will be the first one that will be capable of doing that, in just a demo, it’s generally useful in day-to-day life."

Nic Cruz Patane

120,088 次观看 • 26 天前

Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at hello@qualiastudios.dev More soon

Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at [email protected] More soon

Qualia

87,750 次观看 • 2 个月前

Memo is a robot that uses AI to perform household tasks effectively. Today Sunday announced its Series B, and we’re proud to be investors. Training robots for the home is hard — the environment is messy, dynamic, and full of edge cases. So Sunday is training robots directly on real households. Founders Tony Zhao and Cheng Chi built a glove-based system that lets hundreds of contributors record everyday tasks in their own homes, creating high-fidelity demonstrations that feed directly into robot learning. Home robotics will be defined by the companies that learn fastest from real homes. Sunday is building that loop. More here: Aaref Hilaly Amanda Huang

Memo is a robot that uses AI to perform household tasks effectively. Today Sunday announced its Series B, and we’re proud to be investors. Training robots for the home is hard — the environment is messy, dynamic, and full of edge cases. So Sunday is training robots directly on real households. Founders Tony Zhao and Cheng Chi built a glove-based system that lets hundreds of contributors record everyday tasks in their own homes, creating high-fidelity demonstrations that feed directly into robot learning. Home robotics will be defined by the companies that learn fastest from real homes. Sunday is building that loop. More here: Aaref Hilaly Amanda Huang

Bain Capital Ventures

21,847 次观看 • 5 个月前

In the future, it might just be humanoid robots doing the refueling!🤖⛽️ Sinopec plans to introduce humanoid robot workers across its gas stations. They will handle tasks like fueling, picking up items, restocking, and inspections,working alongside human staff, especially during peak holiday periods in China to ease service pressure. With more than 30,000 gas stations across the country (most of them equipped with convenience stores), this implies a deployment of at least 30,000 humanoid robots. The robot is a wheeled humanoid developed by Beijing-based company FIVEAGES.

In the future, it might just be humanoid robots doing the refueling!🤖⛽️ Sinopec plans to introduce humanoid robot workers across its gas stations. They will handle tasks like fueling, picking up items, restocking, and inspections,working alongside human staff, especially during peak holiday periods in China to ease service pressure. With more than 30,000 gas stations across the country (most of them equipped with convenience stores), this implies a deployment of at least 30,000 humanoid robots. The robot is a wheeled humanoid developed by Beijing-based company FIVEAGES.

CyberRobo

23,536 次观看 • 4 个月前

Imagine you go to a store and you want to buy candy. The shopkeeper knows you're a real kid because they can see you standing right there. Now imagine you send a robot to buy candy for you. The shopkeeper looks at the robot and thinks: wait, who sent this? Is this robot allowed to buy candy? What if someone else's robot pretends to be yours and steals your candy money? That's basically what's happening with AI right now. Companies like Visa let people buy things all over the world. But now, smart computer robots (AI agents) want to buy things too. Shop around, compare prices, even pay for stuff. Visa looked at this and said: nope, not yet. Because they have no way to check if the robot is real, who it belongs to, or if it's allowed to spend that money. The problem is that all the rules we have for checking identity - showing your ID, scanning your face, typing your password - only work for humans. Robots can't do any of that. Worse, bad robots can actually copy and fake human identities really well. So Evin McMullen evin, Billions Network co-founder and CEO, says we need a new kind of ID system. One where you can prove something is true without showing all your private stuff. Like proving you're tall enough for a ride without telling anyone your exact height. That's called zero-knowledge proof. And for the robots specifically, we need something called KYA - Know Your Agent. It's like giving every robot its own ID card that says: this is who I am, this is what I'm allowed to do, and this is the human responsible for me. Until we build that, the robot economy can't really get going. Here is Evin’s Thought Leader article at Silicon Valleys Journal

Imagine you go to a store and you want to buy candy. The shopkeeper knows you're a real kid because they can see you standing right there. Now imagine you send a robot to buy candy for you. The shopkeeper looks at the robot and thinks: wait, who sent this? Is this robot allowed to buy candy? What if someone else's robot pretends to be yours and steals your candy money? That's basically what's happening with AI right now. Companies like Visa let people buy things all over the world. But now, smart computer robots (AI agents) want to buy things too. Shop around, compare prices, even pay for stuff. Visa looked at this and said: nope, not yet. Because they have no way to check if the robot is real, who it belongs to, or if it's allowed to spend that money. The problem is that all the rules we have for checking identity - showing your ID, scanning your face, typing your password - only work for humans. Robots can't do any of that. Worse, bad robots can actually copy and fake human identities really well. So Evin McMullen evin, Billions Network co-founder and CEO, says we need a new kind of ID system. One where you can prove something is true without showing all your private stuff. Like proving you're tall enough for a ride without telling anyone your exact height. That's called zero-knowledge proof. And for the robots specifically, we need something called KYA - Know Your Agent. It's like giving every robot its own ID card that says: this is who I am, this is what I'm allowed to do, and this is the human responsible for me. Until we build that, the robot economy can't really get going. Here is Evin’s Thought Leader article at Silicon Valleys Journal

Billions Network

21,775 次观看 • 6 个月前

Japan Airlines is starting a new 2 year program integrating humanoid robots at at Tokyo's Haneda Airport The robots will help with baggage handling and cleaning aircrafts Early demonstrations showed the robots are still clumsy with wobbly walking and basic movements. Their goal is to test how well they adapt to real airport environments without major infrastructure changes If this program is a success it will likely lead to wider deployment Technology like this is only going to expand and it’s going to keep replacing jobs

Japan Airlines is starting a new 2 year program integrating humanoid robots at at Tokyo's Haneda Airport The robots will help with baggage handling and cleaning aircrafts Early demonstrations showed the robots are still clumsy with wobbly walking and basic movements. Their goal is to test how well they adapt to real airport environments without major infrastructure changes If this program is a success it will likely lead to wider deployment Technology like this is only going to expand and it’s going to keep replacing jobs

Wall Street Apes

19,519 次观看 • 3 个月前

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

It's 2030 and you are reviewing humanoid robots. A Tesla. A Google. An Apple. An OpenAI. A Meta. A Figure. And a bunch of Chinese-made ones. Which one is best, and why? I think the Tesla understands the world much better. Why? There were eight Teslas around me on the freeway today. Start there. No other robot company has that data. But my robot is parked at the local high school twice a day. Its cameras see humans in all of our weirdness. How we move. Where we go. Where we walk. Who we talk with. What you are wearing. Whether your hair was combed this morning. That data will lead to robotics breakthroughs. Apple might keep up with its Vision Pro data, but it is too freaked out by the privacy implications of using said data. (On the front are six cameras and a couple of TOF -- Time Of Flight -- sensors that can see everything in your home in great detail). Google has a lot of data, for sure. All my: 1. Email. 2. Calendars. 3. Photos. 4. TV watching behavior. 5. Contacts. 6. Documents and spreadsheets. 7. Files. 8. Location data. So I expect Google's robot will be attractive to many. But how do you see the others shake out over the next five years? Make some guesses. But remember what an AI pioneer told me years ago about AI: it's all about the data. The Chinese ones have huge advantages: the Chinese have more data on their citizens, and many more citizens to boot AND they can make robots cheaper than we can. But now that you know OpenAI is building its own robot you have caught wind of what I've heard from many in San Francisco and Silicon Valley: that humanoid robots are the real prize of AI and will be highly profitable for those that can make them and find customers willing to buy them. Here, too, I learned long ago never to bet against Elon Musk. Will you?

Robert Scoble

33,804 次观看 • 1 年前

If you are wondering why Elon Musk has focused all his energy and wealth on producing reusable rockets, AI, and robots… Recently, he announced that they will stop the production of some car models and replace it with robot production. The robots will become their workforce and guards. The bunkers will be underground, but the safest bet during a Geophysical Event is to be in space and return later, once everything settles down.

If you are wondering why Elon Musk has focused all his energy and wealth on producing reusable rockets, AI, and robots… Recently, he announced that they will stop the production of some car models and replace it with robot production. The robots will become their workforce and guards. The bunkers will be underground, but the safest bet during a Geophysical Event is to be in space and return later, once everything settles down.

Open Minded Approach

231,949 次观看 • 6 个月前

The next manipulation tool may not live on your screen. It may stand in front of you look into your eyes and convince you that it understands. Would you rather face a humanoid robot strong enough to hurt you or one designed well enough to make you trust it? This robot copies blinking, eye contact, head movement and facial expressions to create the illusion of human presence. That may look impressive but it also opens a darker question. When a machine can look concerned appear friendly and imitate emotion people may start trusting signals that contain no real feeling no empathy and no moral responsibility. So which is more dangerous a robot with physical power or a robot that can manufacture trust? #HumanoidRobot #Robotics #AI

The next manipulation tool may not live on your screen. It may stand in front of you look into your eyes and convince you that it understands. Would you rather face a humanoid robot strong enough to hurt you or one designed well enough to make you trust it? This robot copies blinking, eye contact, head movement and facial expressions to create the illusion of human presence. That may look impressive but it also opens a darker question. When a machine can look concerned appear friendly and imitate emotion people may start trusting signals that contain no real feeling no empathy and no moral responsibility. So which is more dangerous a robot with physical power or a robot that can manufacture trust? #HumanoidRobot #Robotics #AI

Techniahqrobot | humanoid robots

11,650 次观看 • 26 天前

Hey #NeuraxonMini is literally out! , we manage to "transplant" a Neuraxon 2 bioinspired #AI brain to a physical robot the #SpheroMini moving from our last Scientific Paper (link bellow) by David Vivancos - e/acc & Jose Sánchez for Qubic #OpenScience hybridized with #Aigarth to the real World. First you need a Sphero Education Mini robot about 50$ Then you can try the first cool demos at Hugging Face: 1.- Neuraxon2MiniControl to drive the sphero robot 2.- Neuraxon2MiniWrite to write letters or words with physical moves of the sphero robot using Neuraxon Video Tutorials on youtube later today. Why this matters? Remember we are not building "dead" LLMs we are building #AliveAIs and for that we need to explore how it behaves in reality, from how it learns to how it fails, and what better way that in the emerging field of #robotics , time will tell if your next #HumanoidRobot have a #Neuraxon brain... Read the Paper: Explore the Neuraxon code here: Are you ready for #TrueAI ?

Hey #NeuraxonMini is literally out! , we manage to "transplant" a Neuraxon 2 bioinspired #AI brain to a physical robot the #SpheroMini moving from our last Scientific Paper (link bellow) by David Vivancos - e/acc & Jose Sánchez for Qubic #OpenScience hybridized with #Aigarth to the real World. First you need a Sphero Education Mini robot about 50$ Then you can try the first cool demos at Hugging Face: 1.- Neuraxon2MiniControl to drive the sphero robot 2.- Neuraxon2MiniWrite to write letters or words with physical moves of the sphero robot using Neuraxon Video Tutorials on youtube later today. Why this matters? Remember we are not building "dead" LLMs we are building #AliveAIs and for that we need to explore how it behaves in reality, from how it learns to how it fails, and what better way that in the emerging field of #robotics , time will tell if your next #HumanoidRobot have a #Neuraxon brain... Read the Paper: Explore the Neuraxon code here: Are you ready for #TrueAI ?

David Vivancos - e/acc

29,293 次观看 • 5 个月前

Can robots learn without training❓ [𝗜𝘁'𝘀 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲𝗱 ⬇ ] Teaching robots to do complex tasks WITHOUT spending hours training them. Sounds cool, right? That's exactly what DIAL-MPC does! The first training-free method for whole-body torque control using full-order dynamics: ✅ Instantly checks if a robot's moves are right or wrong ✅ Adapts quickly to new tasks without needing extra training ✅ Could work hand-in-hand with other robot learning methods Robots are getting smarter AND faster without the need for long training sessions. Website: Paper: Code: Saw this first Haoru Xue ✈️ CVPR 🙏

Can robots learn without training❓ [𝗜𝘁'𝘀 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲𝗱 ⬇ ] Teaching robots to do complex tasks WITHOUT spending hours training them. Sounds cool, right? That's exactly what DIAL-MPC does! The first training-free method for whole-body torque control using full-order dynamics: ✅ Instantly checks if a robot's moves are right or wrong ✅ Adapts quickly to new tasks without needing extra training ✅ Could work hand-in-hand with other robot learning methods Robots are getting smarter AND faster without the need for long training sessions. Website: Paper: Code: Saw this first Haoru Xue ✈️ CVPR 🙏

Ilir Aliu

71,502 次观看 • 1 年前

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

Rohan Paul

37,121 次观看 • 6 个月前