Dale Schuurmans

Dale Schuurmans explores the relationship between large language models and computational theory, examining what language models can and cannot compute. The talk investigates the computational capabilities and limitations of modern LLMs from a theoretical perspective, with implications for how RL agents might leverage language models for planning and decision-making.

Dale Schuurmans is a Professor of Computing Science at the University of Alberta, a Research Director at Google DeepMind, and a Fellow of Amii. His research spans machine learning, optimization, and artificial intelligence, with particular focus on the intersection of large language models and reinforcement learning.

He has published over 200 papers and received several best paper awards at top conferences. His work on combining language models with decision-making has been influential in the recent surge of foundation model research.