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🚨🚨🚨Humanoid Robots Just Stepped Into the Ring** This is not really a fight. Not yet. The robots are slow, awkward, unstable, and clearly still learning how to move like athletes. But that is exactly what makes the clip interesting. A boxing ring is one of the hardest places to...

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15,095 görüntüleme • 24 gün önce •via X (Twitter)

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The humanoid race is not about robots. It is about collecting physical data. Today they move boxes. Tomorrow they assemble cars, repair machines and work beside humans. Every warehouse shift is another dataset. Every failed grasp is another training example. The companies that collect the most real-world physical data today will build the smartest robots tomorrow.
0:59

The humanoid race is not about robots. It is about collecting physical data. Today they move boxes. Tomorrow they assemble cars, repair machines and work beside humans. Every warehouse shift is another dataset. Every failed grasp is another training example. The companies that collect the most real-world physical data today will build the smartest robots tomorrow.

Fluixo

39,997 görüntüleme • 1 ay önce

Four Optimus robots. One factory floor. 🤖🏭 Walking, carrying, and working side by side — all at the same time. No teleoperation. No humans controlling every move. Just humanoid robots learning to work together in the real world. This isn’t one robot doing a demo anymore. The future is building the factory.
0:47

Four Optimus robots. One factory floor. 🤖🏭 Walking, carrying, and working side by side — all at the same time. No teleoperation. No humans controlling every move. Just humanoid robots learning to work together in the real world. This isn’t one robot doing a demo anymore. The future is building the factory.

DN_DEGEN

36,993 görüntüleme • 8 gün önce

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:56

Brain-controlled exoskeletons to train humanoid robots! 🧠 Fourier just presented human tele-operators using brain control interfaces and exoskeletal arms to train humanoid robots on home tasks. The brain control interface is the interesting part. Instead of using a controller or joystick to teleoperate, the operator's movements and intentions are captured more naturally through the exoskeleton and BCI. This means the demonstrations are more fluid, more human-like, and better suited for training robots to perform delicate home tasks. Multiple tele-operators are simultaneously generating training data across multiple robots. This is how you build the dataset needed for eventual full autonomy, without waiting years for it to arrive. This might be the bridge between "robots that work in controlled environments" and "robots that work in homes." Not full autonomy right away, but trusted human intelligence operating through a robot body, getting better with every task completed. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

20,898 görüntüleme • 7 ay önce

Elon Musk says Optimus is the infinite money glitch. Not because robots are valuable. Because robots can make more robots. Musk explained that humanoid robots improve through three exponential trends multiplied together: digital intelligence, AI chip capability, and electromechanical dexterity. But the real unlock is that the robot can start making the robots. "So you have a recursive multiplicative exponential," he said. "This is a supernova." Musk's thesis is that once you have a physical robot capable of manufacturing, the production curve stops being linear and becomes self-replicating. Every robot built accelerates the building of the next one. The implication is that the companies that control physical manufacturing will control AI's future, not the ones with the best models. The bottleneck is not intelligence. It is atoms.
2:07

Elon Musk says Optimus is the infinite money glitch. Not because robots are valuable. Because robots can make more robots. Musk explained that humanoid robots improve through three exponential trends multiplied together: digital intelligence, AI chip capability, and electromechanical dexterity. But the real unlock is that the robot can start making the robots. "So you have a recursive multiplicative exponential," he said. "This is a supernova." Musk's thesis is that once you have a physical robot capable of manufacturing, the production curve stops being linear and becomes self-replicating. Every robot built accelerates the building of the next one. The implication is that the companies that control physical manufacturing will control AI's future, not the ones with the best models. The bottleneck is not intelligence. It is atoms.

Shruti

59,306 görüntüleme • 2 ay önce

HUMANOID ROBOTS ARE AMAZING. BUT WHERE IS THE ROI? Watching a humanoid robot work at BMW is genuinely impressive. As an engineer, I love it. But I also can’t ignore one question. For this task, why not use a 6-axis robot on a linear axis? It would likely be: * Faster. * More precise. * More stable. * Much cheaper. So why the humanoid? Because BMW isn’t optimizing this task. They’re training Physical AI. Every successful grasp, every failure, every unexpected situation becomes data that teaches robots to handle the real world. That’s the real investment. The demo is impressive. The business case? I’m not convinced… yet. Are we looking at the future of manufacturing—or the world’s most expensive AI training program? Best regards Ulrich #HumanoidRobots #PhysicalAI #Robotics #Automation #Manufacturing #Engineering #AI #IndustrialAutomation
0:32

HUMANOID ROBOTS ARE AMAZING. BUT WHERE IS THE ROI? Watching a humanoid robot work at BMW is genuinely impressive. As an engineer, I love it. But I also can’t ignore one question. For this task, why not use a 6-axis robot on a linear axis? It would likely be: * Faster. * More precise. * More stable. * Much cheaper. So why the humanoid? Because BMW isn’t optimizing this task. They’re training Physical AI. Every successful grasp, every failure, every unexpected situation becomes data that teaches robots to handle the real world. That’s the real investment. The demo is impressive. The business case? I’m not convinced… yet. Are we looking at the future of manufacturing—or the world’s most expensive AI training program? Best regards Ulrich #HumanoidRobots #PhysicalAI #Robotics #Automation #Manufacturing #Engineering #AI #IndustrialAutomation

Advanced humanoid forum

11,496 görüntüleme • 1 ay önce

This is already starting. China is pushing humanoid robots into military style demos training grounds and battlefield scenarios. The world is not ready for what comes next. Once robots get legs hands cameras and payload capacity the battlefield changes. No confirmed frontline deployment yet. But the direction is impossible to ignore.
0:47

This is already starting. China is pushing humanoid robots into military style demos training grounds and battlefield scenarios. The world is not ready for what comes next. Once robots get legs hands cameras and payload capacity the battlefield changes. No confirmed frontline deployment yet. But the direction is impossible to ignore.

Techniahqrobot | humanoid robots

576,764 görüntüleme • 2 ay önce

German robotics company NEURA Robotics has created NEURA Gym: a large-scale, physical AI gym and training ground where hundreds of robots, including the humanoid 4NE-1, learn through real-world interactions. The company is collaborating with the Neuraverse ecosystem to create the world's largest repository of physical training data, promoting the application of humanoid robots.
1:39

German robotics company NEURA Robotics has created NEURA Gym: a large-scale, physical AI gym and training ground where hundreds of robots, including the humanoid 4NE-1, learn through real-world interactions. The company is collaborating with the Neuraverse ecosystem to create the world's largest repository of physical training data, promoting the application of humanoid robots.

CyberRobo

73,731 görüntüleme • 10 ay önce

Turning video into humanoid robot motion! 🤳🏼 Training humanoid robots needs huge amounts of motion data, but real-world capture doesn’t scale. Mocap is expensive, dangerous edge cases are rare, and you can’t ask humans to repeatedly fall or crash. Video2Robot tackles this by converting videos into physics-grounded humanoid simulations. Motion is generated to respect balance, inertia, ground contact, and joint limits, then directly retargeted to robot simulators. One prompt can generate a full humanoid motion sequence, including multi-agent interactions and failure cases like falls or collisions, scenarios that are hard or impossible to capture safely in the real world. The pipeline is model-agnostic and works with existing video generators, making it a practical way to scale data for robots. If robots are going to operate in the real world, they need to be trained on the failures too, not just the perfect demos. Here's the GitHub: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:26

Turning video into humanoid robot motion! 🤳🏼 Training humanoid robots needs huge amounts of motion data, but real-world capture doesn’t scale. Mocap is expensive, dangerous edge cases are rare, and you can’t ask humans to repeatedly fall or crash. Video2Robot tackles this by converting videos into physics-grounded humanoid simulations. Motion is generated to respect balance, inertia, ground contact, and joint limits, then directly retargeted to robot simulators. One prompt can generate a full humanoid motion sequence, including multi-agent interactions and failure cases like falls or collisions, scenarios that are hard or impossible to capture safely in the real world. The pipeline is model-agnostic and works with existing video generators, making it a practical way to scale data for robots. If robots are going to operate in the real world, they need to be trained on the failures too, not just the perfect demos. Here's the GitHub: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

59,835 görüntüleme • 8 ay önce

A planetary roller screw looks simple, but it’s one of the key enablers for humanoid robots. It converts rotational motion into precise linear motion with high efficiency, high load capacity, and extremely smooth control. In humanoid robots, this is exactly what you need for: joint actuation linear actuators in arms/legs high-force, high-precision movement under continuous cycles Compared to ball screws, it offers better durability and load distribution—critical for robots that must operate 24/7 in the real world. Small component, huge impact. This is the kind of “hidden hardware” that makes humanoid robotics actually work.
0:57

A planetary roller screw looks simple, but it’s one of the key enablers for humanoid robots. It converts rotational motion into precise linear motion with high efficiency, high load capacity, and extremely smooth control. In humanoid robots, this is exactly what you need for: joint actuation linear actuators in arms/legs high-force, high-precision movement under continuous cycles Compared to ball screws, it offers better durability and load distribution—critical for robots that must operate 24/7 in the real world. Small component, huge impact. This is the kind of “hidden hardware” that makes humanoid robotics actually work.

Steven Cheng

69,970 görüntüleme • 2 ay önce

Godfather of AI Yann LeCun reveals the humanoid robot industry's secret: the companies building the robots have no idea how to make them smart enough to be useful. "There is a lot of expectations that robotics is going to be a revolution, essentially, in a big market, eventually." "But the secret of the industry is that none of the companies at the moment that are building robots, like humanoid robots, none of those companies has any idea how to make those robots smart enough to be useful." "There's a big push for AI to make progress towards... understanding the physical world. That's what is prompting this investment." "There's nothing wrong with investing in LLMs. LLMs are useful. They're just addressing a completely different set of applications, really." LeCun is not describing someone else's problem. He has spent 15 years on world models, raised more than $1 billion for AMI Labs to build that missing intelligence layer, and in the same interview he calls 2026 the year of the world model and puts consumer robots 3 to 5 years out. Every humanoid robot demo you have seen is a body waiting for a brain. The winner in robotics will not be the company that shipped the body; it will be the one that ships the intelligence. - Yann LeCun (Yann LeCun), Turing Award winner and founder of AMI Labs, on Bloomberg Television.
1:01

Godfather of AI Yann LeCun reveals the humanoid robot industry's secret: the companies building the robots have no idea how to make them smart enough to be useful. "There is a lot of expectations that robotics is going to be a revolution, essentially, in a big market, eventually." "But the secret of the industry is that none of the companies at the moment that are building robots, like humanoid robots, none of those companies has any idea how to make those robots smart enough to be useful." "There's a big push for AI to make progress towards... understanding the physical world. That's what is prompting this investment." "There's nothing wrong with investing in LLMs. LLMs are useful. They're just addressing a completely different set of applications, really." LeCun is not describing someone else's problem. He has spent 15 years on world models, raised more than $1 billion for AMI Labs to build that missing intelligence layer, and in the same interview he calls 2026 the year of the world model and puts consumer robots 3 to 5 years out. Every humanoid robot demo you have seen is a body waiting for a brain. The winner in robotics will not be the company that shipped the body; it will be the one that ships the intelligence. - Yann LeCun (Yann LeCun), Turing Award winner and founder of AMI Labs, on Bloomberg Television.

Karl Mehta

44,425 görüntüleme • 1 ay önce

1958, The Robot Guest. This Robbie The Robot influenced many ideas of how we see and react to robots even today. It is also one reason anthropomorphic bipedal humanoid robots are easier psychologically.
0:36

1958, The Robot Guest. This Robbie The Robot influenced many ideas of how we see and react to robots even today. It is also one reason anthropomorphic bipedal humanoid robots are easier psychologically.

Brian Roemmele

19,785 görüntüleme • 9 ay önce

Not all of the humanoid robots entered into the marathon in China made it ! Here is one of the ‘casualties’ Try not to laugh !🤣
0:22

Not all of the humanoid robots entered into the marathon in China made it ! Here is one of the ‘casualties’ Try not to laugh !🤣

Andrew Bridgen

24,312 görüntüleme • 4 ay önce

⚠️ ONE HUMANOID ROBOT IS IMPRESSIVE. WATCHING AN ENTIRE FLEET MOVE AS ONE IS A DIFFERENT LEVEL. Dozens of humanoid robots are performing the same sequence simultaneously, matching their timing across the entire formation. Every step, arm movement and change of position has to stay coordinated while each machine independently maintains its balance. One robot can hide a mistake - a whole formation can't. The choreography is almost beside the point. What you're really seeing is the ability to reproduce complex physical movements consistently across a large number of machines, without the formation falling apart. That kind of repeatability becomes far more important once robots move from controlled demonstrations into real industrial environments. And that's where the real breakthrough could be. The future of humanoid robotics won't be measured only by what one machine can do, but by how reliably an entire fleet can do it. One capable robot is a technological achievement; coordinating many of them turns that capability into a system. One robot proves the technology. A fleet shows what happens when it scales.
1:44

⚠️ ONE HUMANOID ROBOT IS IMPRESSIVE. WATCHING AN ENTIRE FLEET MOVE AS ONE IS A DIFFERENT LEVEL. Dozens of humanoid robots are performing the same sequence simultaneously, matching their timing across the entire formation. Every step, arm movement and change of position has to stay coordinated while each machine independently maintains its balance. One robot can hide a mistake - a whole formation can't. The choreography is almost beside the point. What you're really seeing is the ability to reproduce complex physical movements consistently across a large number of machines, without the formation falling apart. That kind of repeatability becomes far more important once robots move from controlled demonstrations into real industrial environments. And that's where the real breakthrough could be. The future of humanoid robotics won't be measured only by what one machine can do, but by how reliably an entire fleet can do it. One capable robot is a technological achievement; coordinating many of them turns that capability into a system. One robot proves the technology. A fleet shows what happens when it scales.

Future Memo

16,337 görüntüleme • 24 gün önce

Nerds are building super athletes to take your job. AI agents are coming for knowledge workers and humanoid robots are coming for blue collar work. You may not like it, but that is where the world is headed.
2:43

Nerds are building super athletes to take your job. AI agents are coming for knowledge workers and humanoid robots are coming for blue collar work. You may not like it, but that is where the world is headed.

Anthony Pompliano 🌪

45,537 görüntüleme • 8 ay önce

This is HUGE 🚨 just announced 4 robots, each one capable of doing real-world tasks. Not demos. Real deployments. This is how the industry is being shaped:
1:14

This is HUGE 🚨 just announced 4 robots, each one capable of doing real-world tasks. Not demos. Real deployments. This is how the industry is being shaped:

GrowAIHub

525,942 görüntüleme • 10 ay önce

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.
2:32

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.

Karl Mehta

14,140 görüntüleme • 2 ay önce