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Disney is doing what only Disney can: spending massive R&D budgets to make robots "lovable." 💸🤖 By solving the physics of character animation with Olaf, they are creating the blueprint for mainstream acceptance. Here is how startups like Cartwheel, Sunday & Tangible are following that lead to get robots...

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60,341 görüntüleme • 8 ay önce •via X (Twitter)

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Simulating and training robots requires a physics-first approach. 🤖 With Newton, the open-source physics simulation engine co-developed by Disney Research, Walt Disney Imagineering, Google DeepMind and NVIDIA, Disney’s BDX Droid can move through shifting sand and gravel with exceptional precision. Watch to see how Newton is playing a key role in teaching robots how to move, behave, and interact with different objects and materials in the real world. #CES2026
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Simulating and training robots requires a physics-first approach. 🤖 With Newton, the open-source physics simulation engine co-developed by Disney Research, Walt Disney Imagineering, Google DeepMind and NVIDIA, Disney’s BDX Droid can move through shifting sand and gravel with exceptional precision. Watch to see how Newton is playing a key role in teaching robots how to move, behave, and interact with different objects and materials in the real world. #CES2026

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Are you ready for the Bad Mad Robot invasion? 🤖 We tested the closed beta with many legends. BADMAD ROBOTS is pushing the challenge! It was my pleasure to be there. You can see how you can get many rewards such as Closed Beta, Ambassador Program and ROBOTS BOX in the article below 👇

TSUBASA 🥷🎮

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From rugged terrain to soft fabrics, this droid handles it all. 🤖 With Newton, the open-source physics simulation engine co-developed by Google DeepMind and Disney Research, Walt Disney Imagineering, robots can move through shifting sand or gravel and manipulate delicate materials with greater precision than ever before. Learn how Newton is advancing robot learning and shaping the next generation of robotic systems. Watch it in action with Disney’s BDX Droid: #NVIDIAGTC
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From rugged terrain to soft fabrics, this droid handles it all. 🤖 With Newton, the open-source physics simulation engine co-developed by Google DeepMind and Disney Research, Walt Disney Imagineering, robots can move through shifting sand or gravel and manipulate delicate materials with greater precision than ever before. Learn how Newton is advancing robot learning and shaping the next generation of robotic systems. Watch it in action with Disney’s BDX Droid: #NVIDIAGTC

NVIDIA Robotics

53,955 görüntüleme • 8 ay önce

Robots and smart devices are about to get a massive upgrade. 🤖 Forget clunky GPS or special markers. We’re talking about machines that can understand their exact position & orientation in the real world just by SEEING IT. This is the future of machine perception, and it's happening now. 👇
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Robots and smart devices are about to get a massive upgrade. 🤖 Forget clunky GPS or special markers. We’re talking about machines that can understand their exact position & orientation in the real world just by SEEING IT. This is the future of machine perception, and it's happening now. 👇

Over the Reality 🌐

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Pre-programmed backflips are fun, but open-ended reasoning is the real challenge for robots. 🤖 Hannah Fry stepped inside the lab to see how we’re building agents that can understand context and figure things out for themselves – rather than just following a script. Watch our bonus episode ↓
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Pre-programmed backflips are fun, but open-ended reasoning is the real challenge for robots. 🤖 Hannah Fry stepped inside the lab to see how we’re building agents that can understand context and figure things out for themselves – rather than just following a script. Watch our bonus episode ↓

Google DeepMind

228,190 görüntüleme • 8 ay önce

Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”
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Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”

Sawyer Merritt

250,956 görüntüleme • 6 ay önce

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”
1:20

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”

Teslaconomics

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Meet the world at home, where life happens and bots become family 35 days ago, at our “Born to Bot, Bot to Family” launch event, we shared our vision of bringing robots into real homes. Today, we’re very happy to share that our robots are now gradually entering real families. For embodied AI, the real world is everyday life: different routines, different kitchens, and different ways of doing even the simplest tasks. This is where robots meet the world at home, where life happens and bots become family. They are still learning. They may move slowly, hesitate, and sometimes look a little clumsy. But every home they enter helps them understand the world a little better.
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Meet the world at home, where life happens and bots become family 35 days ago, at our “Born to Bot, Bot to Family” launch event, we shared our vision of bringing robots into real homes. Today, we’re very happy to share that our robots are now gradually entering real families. For embodied AI, the real world is everyday life: different routines, different kitchens, and different ways of doing even the simplest tasks. This is where robots meet the world at home, where life happens and bots become family. They are still learning. They may move slowly, hesitate, and sometimes look a little clumsy. But every home they enter helps them understand the world a little better.

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Elon Musk revealed the 3 hardest challenges for humanoid robots and how Tesla is solving them There are really only three hard things for humanoid robots: - Real-world intelligence - ⁠The hand and - ⁠Scale manufacturing "I haven’t seen any demo robots that have a great hand with all the degrees of freedom of a human hand. But Optimus does have that" To reach human-level dexterity, Tesla had to design custom actuators, motors, gears, power electronics, controls, and sensors, everything from physics first principles There is no supply chain for this "From an electromechanical standpoint, the hand is more difficult than everything else combined. The human hand turns out to be quite something" This is why Optimus is on a completely different level. Tesla is solving the hardest problems from the ground up
0:55

Elon Musk revealed the 3 hardest challenges for humanoid robots and how Tesla is solving them There are really only three hard things for humanoid robots: - Real-world intelligence - ⁠The hand and - ⁠Scale manufacturing "I haven’t seen any demo robots that have a great hand with all the degrees of freedom of a human hand. But Optimus does have that" To reach human-level dexterity, Tesla had to design custom actuators, motors, gears, power electronics, controls, and sensors, everything from physics first principles There is no supply chain for this "From an electromechanical standpoint, the hand is more difficult than everything else combined. The human hand turns out to be quite something" This is why Optimus is on a completely different level. Tesla is solving the hardest problems from the ground up

X Freeze

20,796 görüntüleme • 5 ay önce

🤖 Meet the UniX AI Panther: a humanoid robot designed to cook meals, prep food, and make your bed using advanced AI and robotic arms. We’ve officially reached the point where robots are moving into our homes to handle daily chores. The future is here but would you actually feel comfortable sleeping in the same house as one of these things?
0:30

🤖 Meet the UniX AI Panther: a humanoid robot designed to cook meals, prep food, and make your bed using advanced AI and robotic arms. We’ve officially reached the point where robots are moving into our homes to handle daily chores. The future is here but would you actually feel comfortable sleeping in the same house as one of these things?

Mario Nawfal

28,137 görüntüleme • 2 ay önce

Sunday Robotics CEO Tony Zhao believes home robots only need to master a handful of chores before they become indispensable. "What is the minimum number of tasks that a robot needs to do to justify its own existence so that people love having it in their homes? I actually think the list is pretty short. The tasks are pretty repetitive. You just need to learn it and just keep doing that over and over again, like folding shirts or loading dishwashers."
1:39

Sunday Robotics CEO Tony Zhao believes home robots only need to master a handful of chores before they become indispensable. "What is the minimum number of tasks that a robot needs to do to justify its own existence so that people love having it in their homes? I actually think the list is pretty short. The tasks are pretty repetitive. You just need to learn it and just keep doing that over and over again, like folding shirts or loading dishwashers."

TBPN

64,079 görüntüleme • 25 gün önce

Another robot from Disney! 🕺🏻 Just look at this dancing fella created by Disney Research. Creating control policies that work on real robots and handling diverse, unseen motions in physics-based character control is still difficult. The Disney team proposes a two-state solution. The first step involves learning a latent space encoding with an autoencoder. After encoding, the policy is trained to map kinematic input to dynamic output, ensuring accurate and adaptable movement. This method eliminates common mode collapse issues and improves motion encoding by separating these stages. This technique has proven effective in real robots in simulations, marking a significant leap forward in robot control. Can't wait for it in action live in 2025 :) ~~~ RT to help 1 robot find a new workplace.
0:39

Another robot from Disney! 🕺🏻 Just look at this dancing fella created by Disney Research. Creating control policies that work on real robots and handling diverse, unseen motions in physics-based character control is still difficult. The Disney team proposes a two-state solution. The first step involves learning a latent space encoding with an autoencoder. After encoding, the policy is trained to map kinematic input to dynamic output, ensuring accurate and adaptable movement. This method eliminates common mode collapse issues and improves motion encoding by separating these stages. This technique has proven effective in real robots in simulations, marking a significant leap forward in robot control. Can't wait for it in action live in 2025 :) ~~~ RT to help 1 robot find a new workplace.

Lukas Ziegler

65,955 görüntüleme • 1 yıl önce

The next frontier of AI is physical. 🤖 From simulation to synthetic data, developers are training robots to understand the real world with NVIDIA Cosmos, Isaac simulation frameworks and open-source physics engine, Newton. Watch the video to see how partners like Hon Hai Technology Group (Foxconn), Hexagon, Humanoid, Noble Machines, and Skild AI are building the future. 🎥
0:51

The next frontier of AI is physical. 🤖 From simulation to synthetic data, developers are training robots to understand the real world with NVIDIA Cosmos, Isaac simulation frameworks and open-source physics engine, Newton. Watch the video to see how partners like Hon Hai Technology Group (Foxconn), Hexagon, Humanoid, Noble Machines, and Skild AI are building the future. 🎥

NVIDIA Robotics

21,664 görüntüleme • 4 ay önce

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.
3:32

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.

The Humanoid Hub

130,388 görüntüleme • 1 yıl önce