AI Pioneer Richard Sutton Launches Lab to Move Beyond Large Language Models

Richard Sutton, a Turing Award-winning computer scientist and a leading figure in artificial intelligence (AI), has announced the formation of a new AI lab focused on developing AI agents that learn continuously from their environment.

The lab, named Oak Lab, is based in Toronto, Canada, and has been founded by Sutton and his former student Khurram Javed. Both previously worked at Keen Technologies, a startup pursuing artificial general intelligence (AGI) founded by legendary gaming developer John Carmack and located in Dallas, Texas, United States.

With this new venture, Sutton is betting that reinforcement learning will define the next phase of AI. He argues that progress depends on moving beyond large language models (LLMs) trained on static datasets toward AI systems that learn from experience. Sutton has previously described current deep learning methods as weak and inefficient.

Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with its environment, receiving rewards or penalties for its actions. This approach is inspired by how humans and animals learn from trial and error.

Sutton is considered a pioneer in reinforcement learning. In 2021, he was awarded the Turing Award—often called the Nobel Prize of computing—along with Andrew Barto for their foundational contributions to the field. His new lab aims to advance AI by focusing on agents that can continuously adapt and improve, rather than relying on fixed datasets.