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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... show more

The Humanoid Hub

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127,482 views • 1 year ago •via X (Twitter)

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nathfavour1 year ago

Physics × robotics 🚀

ARK Electronics2 years ago

Excited about the latest tech for your drone product? Our NDAA-compliant, US-made flight controllers are designed to accelerate your path to market and provide a solid platform for developing your autonomous software. Check them out! #Drones #UAV #UAS #Robotics #MadeInUSA

Djeucharist1 year ago

I always think the guy with the leather biker coat is going to speed off the stage like Meat Loaf in Bat out of Hell.

Atharva Patwe1 year ago

Damnnn son

Aurora1 year ago

🤖📡⚙️

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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

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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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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Olaf made a special appearance on stage with NVIDIA CEO Jensen Huang at #NVIDIAGTC.☃️ NVIDIA and Disney Research are working together to bring this beloved character into the real world using Newton, the open-source physics engine.

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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. 🎥

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Nvidia showcases Blue, a cute little robot powered by the Newton physics engine. This was the „wow“-moment for me. Robots are coming. This time for real. And I am all in for it!

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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.

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CyberRobo

17,092 views • 22 days ago

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The Humanoid Hub

129,383 views • 1 year ago

Robotics: coding agents’ next frontier. So how good are they? We introduce CaP-X: an open-source framework and benchmark for coding agents, where they write code for robot perception and control, execute it on sim and real robots, observe the outcomes, and iteratively improve code reliability. From NVIDIA Berkeley AI Research CMU Robotics Institute Stanford AI Lab 🧵

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Mario Nawfal

38,388 views • 11 months ago

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The Humanoid Hub

18,611 views • 1 year ago

A new paper by Disney Research introduces a 2-stage technique for motion tracking in physics-based character animation, using a pretrained latent space and RL to control diverse and unseen motions on both virtual and real-world humanoid robots. Paper:

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The Humanoid Hub

20,051 views • 1 year ago

This expressive robot designed by Disney is brought to life using the new open-source physics simulator accelerated with NVIDIA's software framework.

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74,378 views • 1 year ago

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163,386 views • 22 days ago

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Lukas Ziegler

22,482 views • 3 months ago

Announced at #GoogleCloudNext: NVIDIA and @GoogleCloud are bringing #agenticAI on-prem with support for Google Gemini models—powered by NVIDIA Blackwell and Confidential Computing for top-tier performance and security. Hear more from our CEO Jensen Huang.

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NVIDIA

75,767 views • 1 year ago

NVIDIA just announced EgoScale 🤖🧠 NVIDIA Research has uncovered a log-linear scaling law for robot dexterity by pretraining VLA models on over 20,000 hours of egocentric human video This massive dataset is 20 times larger than previous efforts and proves that robot intelligence follows a predictable path: the more human data, the lower the loss The secret is a simple recipe combining large-scale human pretraining with a small amount of aligned human-robot mid-training to bridge the gap In testing, this method boosted the average success rate by 54% on a 22-DoF robotic hand compared to policies built without pretraining EgoScale also enables one-shot task adaptation and works across different hardware, suggesting that human motion is a universal motor prior for robots Website: Paper: Source: NVIDIA Research #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #NVIDIA #EgoScale #GR00T

NVIDIA just announced EgoScale 🤖🧠 NVIDIA Research has uncovered a log-linear scaling law for robot dexterity by pretraining VLA models on over 20,000 hours of egocentric human video This massive dataset is 20 times larger than previous efforts and proves that robot intelligence follows a predictable path: the more human data, the lower the loss The secret is a simple recipe combining large-scale human pretraining with a small amount of aligned human-robot mid-training to bridge the gap In testing, this method boosted the average success rate by 54% on a 22-DoF robotic hand compared to policies built without pretraining EgoScale also enables one-shot task adaptation and works across different hardware, suggesting that human motion is a universal motor prior for robots Website: Paper: Source: NVIDIA Research #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #NVIDIA #EgoScale #GR00T

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