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In this video, we break down GR00T-N1, NVIDIA’s open foundation model for generalist humanoid robots. We explore how this Vision-Language-Action (VLA) model combines a powerful vision-language backbone with a diffusion-based action policy, how the data pyramid unifies web videos, synthetic data, and real robot trajectories, and why this approach is a big step toward truly general-purpose humanoid robots. You’ll learn: What GR00T-N1 is and what problem it solves in robot learning How the dual System-1 / System-2 architecture works in practice How NVIDIA generates massive synthetic neural trajectories from just 88 hours of teleoperation data How GR00T-N1 performs versus state-of-the-art imitation learning baselines in simulation and on real GR-1 humanoids What’s open-sourced and how you can experiment with the model yourself 🔗 Original paper (arXiv) GR00T N1: An Open Foundation Model for Generalist Humanoid Robots: https://arxiv.org/abs/2503.14734 🔗 Official NVIDIA GR00T repo (code & docs) Isaac GR00T (includes N1 code via the n1-release branch): https://github.com/NVIDIA/Isaac-GR00T 🔗 Pretrained GR00T-N1 model checkpoint Hugging Face – nvidia/GR00T-N1-2B: https://huggingface.co/nvidia/GR00T-N... (Optionally also mention newer N1.5 resources for viewers wanting the latest version.) If you enjoy deep dives into cutting-edge AI and robotics papers, don’t forget to like, subscribe, and turn on notifications so you don’t miss the next breakdown! #nvidia #GR00T #humanoidrobots #robotics #airesearch #vla #embodiedai #groot