NVIDIA Robotics inspires visionaries and developers to create the next generation of AI-driven robots and explore the world of physical AI.

Santa Clara, CA
Joined November 2009
NVIDIA announces new Isaac tools for agents as Agile Robots unveils Agile ONE SN, a reference humanoid for robotics research. 🦾 Built on NVIDIA Isaac GR00T and powered by Jetson Thor, Agile ONE SN gives researchers and developers an integrated platform to develop, train and validate humanoid skills. The Isaac expansion also introduces new datasets, a runtime, and robot learning framework updates to accelerate development from data to deployment. Read the #NVIDIAGTC announcement: nvidianews.nvidia.com/news/n…
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💚 Microducks
From prompt → to sim → to Jensen’s GTC stage. 🦆 Microduck is a 25 cm open-source robot you can train yourself with Isaac Lab. See how 👀⤵️
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Run bigger AI models with less memory on NVIDIA Jetson. Join us live with @RidgeRunX and @ConnectTechInc to explore model quantization, efficient inference runtimes, and NVIDIA Jetson Agent Skills. See how large vision-language models fit into less memory and how memory optimization supports a real robotics application. Bring your questions and learn how to make room for more AI. 🕛 Thursday, 10/29 at 11:00 AM PT 📅 Add to calendar: nvda.ws/4jOFBO9
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What’s new in NVIDIA Isaac Lab 3.0? Join our Robotics Office Hours for a closer look at multi-physics support, multi-rendering support, and RL post-training. We’ll walk through examples and share learning resources to help you get started. Bring your robot learning questions. 🕧 Wednesday at 11:00 AM PT 🔗 nvda.ws/4zWKDwJ
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NVIDIA Robotics retweeted
Join us at Altera Innovators Day in San Jose on October 28 and hear from featured speaker Deepu Talla, VP and GM of Robotics and Edge AI at NVIDIA. Register Today. go.altera.com/innovators-day…
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Exciting to see NVIDIA Cosmos 3 Nano put to the test in the WorldOracle benchmark, comparing its predictions with real-world executions on the Agibot G2 robot. 🎉
We adapt and evaluate Cosmos 3 Nano in WorldOracle. We initialize it from the official 16B checkpoint and compare its predicted rollouts with paired real-world executions. #NVIDIACosmos #PhysicalAI
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Isaac Lab 3.0 tutorial released! Link in bio @NVIDIARobotics
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Helpful robots, sleepy ducks. 🦆🤖 Everyone had a favorite.
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Little ducks. Big conference. 🦆 #NVIDIAGTC
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Now that’s a lineup. 💚 A spotlight on a few of our robotics and automotive partners from Europe and around the world as we celebrate the entire ecosystem bringing physical AI to life. To all our partners, thanks for building with us and making moments like this possible. #NVIDIAGTC
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NVIDIA Robotics retweeted
From autonomous vehicles to smarter factories, companies are putting physical AI to work. We’ve added new NVIDIA Cosmos tools to help developers generate training data, train world models and test them before deployment. See how @Porsche, @MercedesBenz, @encord_team, @Siemens, @fogsphere, and @ltx_io are using Cosmos across robotics, autonomous driving and factory operations 👇
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🦆 Put AI agents to work to help your robot learn to navigate. Using Microduck as the reference robot, this walkthrough shows how to create a simulated obstacle course with @OpenAI GPT-6 Astra, build 3D assets with @nvidiaomniverse libraries, simulate physics with Newton, train policies in NVIDIA Isaac Lab, and validate them in Isaac Sim on @NVIDIARTXSpark.
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Want to try Nemotron 3.5 Bolt E4B 4GB for yourself? 👀 Get hands-on with it on your NVIDIA Jetson through Jetson AI Labs: jetson-ai-lab.com/models/Nem…
Available now: NVIDIA Nemotron 3.5 Bolt E4B 4GB ⚡️ Our newest small open model is built for local assistants, interactive characters and robots that can carry on a conversation and use tools to get things done. Watch Reachy Mini chat and move, with Bolt handling conversation and NVIDIA Cosmos handling vision. Both models run locally on Jetson Orin Nano 8GB. Learn more: research.nvidia.com/labs/nem…
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We’re excited to announce the official release of NVIDIA Isaac Lab 3.0. 🎉 Isaac Lab 3.0 brings a new modular and lightweight architecture along with major new capabilities across the robot learning workflow: multi-physics and multi-rendering support, training at scale, and streamlined deployment on real hardware. With Newton integration, the new OVRTX renderer, RL post-training, and LEAPP deployment, there’s a lot to explore. Here’s a look at what’s new 🧵 (1/7)
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Large robot foundation models like NVIDIA Isaac GR00T bring knowledge and skills from pretraining. Isaac RL Post Training (RLPT) builds on that foundation with reinforcement learning. Isaac Lab enables these large models to practice at scale through parallel simulation and allows them to refine their existing skills. (6/7)
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Isaac Lab 3.0 connects training in simulation to deployment on real hardware through LEAPP, which packages a policy’s compute graph and metadata into a portable deployment bundle. Here, that workflow takes a policy from Isaac Lab to real hardware, bringing the thread from choosing your simulation backends all the way to putting learned skills into action. Get started with Isaac Lab 3.0: github.com/isaac-sim/IsaacLa… (7/7)
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