Eureka! Extreme Robot Dexterity with LLMs | NVIDIA Research Paper

A new AI agent developed by NVIDIA Research that can teach robots complex skills has trained a robotic hand to perform rapid pen-spinning tricks — for the first time as well as a human can. The stunning prestidigitation, showcased in the video above, is one of nearly 30 tasks that robots have learned to expertly accomplish thanks to Eureka, which autonomously writes reward algorithms to train bots. Eureka has also taught robots to open drawers and cabinets, toss and catch balls, and manipulate scissors, among other tasks. The Eureka research, published today, includes a paper and the project’s AI algorithms, which developers can experiment with using NVIDIA Isaac Gym, a physics simulation reference application for reinforcement learning research. Isaac Gym is built on NVIDIA Omniverse, a development platform for building 3D tools and applications based on the OpenUSD framework. Eureka itself is powered by the GPT-4 large language model. Read the blog: Eureka project on GitHub: Join the NVIDIA Developer Program: Read and subscribe to the NVIDIA Technical Blog: Research, Autonomous Machines, Deep Learning, Artificial Intelligence, Generative AI, Isaac, NVIDIA Research, Omniverse, Open Source, Robotics, Simulation and Design, LLM, Sim2real, Isaac Sim, #Robotics, #LLM, #AI, #sim2real, #NVIDIAOmniverse