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From Robot Development to Deployment with Isaac GR00T & Jetson Thor
SITUATION DETECTED: LG is developing a next-generation bipedal humanoid robot built on Nvidia’s Isaac GR00T foundation model, with a public unveiling planned for Q1 2027.
🔥 JUST IN: LG partners with NVIDIA to unveil a next-gen bipedal humanoid robot built on Isaac GR00T, targeting a public debut in Q1 next year.
Building general-purpose humanoid robots requires an end-to-end approach. Join NVIDIA’s Spencer Huang to see how AI agents and NVIDIA Isaac GR00T are accelerating the entire process. Add the session to your calendar 👉
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Ready to take robots from development to deployment? Join our livestream on August 26 at 9 a.m. PT to learn how to: 🧠 Develop and deploy robots with NVIDIA Isaac GR00T and Jetson Thor 🏭 Apply sim to real workflows for industrial robotics 🦾 Turn teleoperation data into real robot actions 🎙️ See @NobleMachines and @seeedstudio demonstrate practical robotics workflows across humanoids and robotic arms. Watch live:
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Unitree Introducing | Unitree H2 Plus Integrated R&D and Manufacturing, Embarking on Full-Stack Development🥳 Unitree Robotics announces H2 Plus, the first humanoid robot reference design built on @NVIDIA Isaac GR00T to accelerate humanoid research. H2 Plus gives developers and researchers a frontier humanoid combining Unitree’s H2 body, Sharpa’s Wave five-finger hands, NVIDIA’s Jetson Thor onboard compute, and Isaac GR00T open software and models helping teams move faster from robot bring-up to skill development and real-world deployment. Learn more:
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This week at #CVPR2026#, NVIDIA Research is presenting three papers across physical ai that offer groundbreaking solutions for training at scale across diverse applications: → GraspGen-X: the first foundation model for zero-shot grasping, trained on billions of simulated grasps → LCDrive: a model that replaces expensive text-based reasoning with compact latent representations → NitroGen: a generalized gameplay AI foundation model that harnesses NVIDIA Isaac GR00T to help train embodied agents Learn more:
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