How to Train Scientific Agents with Reinforcement Learning

NVIDIA released NeMo Gym and NeMo RL as open-source libraries to train AI agents for scientific research using reinforcement learning, addressing the challenge of building reliable scientific assistants that can handle complex, multi-step research tasks. These tools enable researchers to create realistic training environments where agents learn to perform scientific workflows like literature review, experiment planning, and data analysis, with Edison Scientific already using the framework to develop Aviary for automating scientific discovery across biology and chemistry domains.