Nvidia researchers introduce ENPIRE, a framework for autonomous robot training by AI agents
Nvidia researchers, in collaboration with Carnegie Mellon and UC Berkeley, have introduced ENPIRE, a framework allowing AI coding agents to autonomously train robots. A researcher stated that the platform "completely excludes human participation in the training loop," creating a self-improving system. ENPIRE uses four core modules responsible for environment preparation, policy improvement, testing, and evolution. Coding agents analyze logs, read scientific papers, and optimize code to refine physical robot control without manual programming. In trials at Nvidia's GEAR Lab, a fleet of 8 physical robots achieved a 99% success rate on complex tasks like cutting cables and inserting GPUs. Unlike the 2023 Eureka project, which trained robots only in virtual simulation, ENPIRE runs on physical hardware, proving that scaling robot fleets speeds up learning.
Nvidia research shows robots that train themselves through AI coding agents
