Digital Event Horizon
Hugging Face and NVIDIA have announced a groundbreaking collaboration to accelerate robotics research and development by combining their open-source AI platforms and cutting-edge technology. The partnership aims to drive advances in industries such as manufacturing, healthcare, and logistics, and has the potential to revolutionize the field of robotics.
Hugging Face and NVIDIA collaborate to accelerate robotics research and development.LeRobot combines Hugging Face's open AI framework with NVIDIA's AI technology, simulation, and robotics capabilities.The partnership aims to create a comprehensive suite of tools for sharing data collection, model training, and simulation environments.NVIDIA's Isaac Lab accelerates LeRobot's data collection, training, and verification workflow.Developing physical AI is challenging due to the need for extensive physical interaction data and vision sensors.The collaboration aims to accelerate innovation in AI-powered robotics by building a robot data flywheel.
Hugging Face, a leading open-source AI platform, has recently announced a groundbreaking collaboration with NVIDIA, a renowned leader in the field of artificial intelligence and robotics. The partnership aims to accelerate robotics research and development by combining Hugging Face's LeRobot open AI framework with NVIDIA's cutting-edge AI technology, simulation, and robotics capabilities.
The era of physical AI, where robots can understand the physical properties of environments, is rapidly transforming industries such as manufacturing, healthcare, and logistics. However, developing physical AI requires access to open-source, extensible frameworks that span the development process of robot training, simulation, and inference. Hugging Face's LeRobot platform serves more than 5 million machine learning researchers and developers, offering tools and resources to streamline AI development.
LeRobot extends the successful paradigms from its Transformers and Diffusers libraries into the robotics domain, providing a comprehensive suite of tools for sharing data collection, model training, and simulation environments. Hugging Face users can access and fine-tune the latest pretrained models and build AI pipelines on common APIs with over 1.5 million models, datasets, and applications freely accessible on the Hugging Face Hub.
NVIDIA's AI technology, simulation, and open-source robot learning modular framework, such as NVIDIA Isaac Lab, accelerate the LeRobot's data collection, training, and verification workflow. Researchers and developers can share their models and datasets built with LeRobot and Isaac Lab, creating a data flywheel for the robotics community.
Developing physical AI is challenging due to the need for extensive physical interaction data and vision sensors. Collecting real-world robot data for dexterous manipulation across a large number of tasks and environments is time-consuming and labor-intensive. NVIDIA's Isaac Lab, built on NVIDIA Isaac Sim, enables robot training by demonstration or trial-and-error in simulation using high-fidelity rendering and physics simulation to create realistic synthetic environments and data.
Isaac Lab provides the ability to generate vast amounts of training data — equivalent to thousands of real-world experiences — from a single demonstration. Generated motion data is then used to train a policy with imitation learning. After successful training and validation in simulation, the policies are deployed on a real robot, where they are further tested and tuned to achieve optimal performance.
The iterative process leverages real-world data's accuracy and the scalability of simulated synthetic data, ensuring robust and reliable robotic systems. By sharing these datasets, policies, and models on Hugging Face, a robot data flywheel is created that enables developers and researchers to build upon each other's work, accelerating progress in the field.
"The robotics community thrives when we build together," said Animesh Garg, assistant professor at Georgia Tech. "By embracing open-source frameworks such as Hugging Face's LeRobot and NVIDIA Isaac Lab, we accelerate the pace of research and innovation in AI-powered robotics."
Remi Cadene, principal research scientist at LeRobot, added that combining Hugging Face's open-source community with NVIDIA's hardware and Isaac Lab simulation has the potential to accelerate innovation in AI for robotics.
This work builds on NVIDIA's community contributions in generative AI at the edge, supporting the latest open models and libraries, such as Hugging Face Transformers, optimizing inference for large language models (LLMs), small language models (SLMs), and multimodal vision-language models (VLMs).
Together, Hugging Face and NVIDIA aim to accelerate the work of the global ecosystem of robotics researchers and developers transforming industries ranging from transportation to manufacturing and logistics. The collaboration has already shown promising results, with a physical picking setup being demonstrated using LeRobot software running on NVIDIA Jetson Orin Nano, providing a powerful, compact compute platform for deployment.
Related Information:
https://blogs.nvidia.com/blog/hugging-face-lerobot-open-source-robotics/
https://blogs.nvidia.com/blog/robot-learning-humanoid-development/
Published: Wed Nov 6 11:07:43 2024 by llama3.2 3B Q4_K_M
