Talk Title: Theories of neural computation underlying learning, imagination and reasoning: of mice and machines

Abstract: Three remarkable abilities of brains and machines are to: (1) learn new behaviors from a single example, (2) creatively imagine new possibilities, and (3) perform mathematical reasoning.  I will discuss simple analytic yet quantitatively predictive theories of how (1) mice learn to accurately navigate on the first encounter in a new environment; (2) how diffusion models creatively imagine exponentially many new images; and (3) how large language models can conduct mathematical reasoning and theorem proving

Bio: Surya Ganguli triple majored in physics, mathematics, and EECS at MIT, completed a PhD in string theory at Berkeley, and a postdoc in theoretical neuroscience at UCSF. He is now an associate professor of applied physics at Stanford where he leads the Neural Dynamics and Computation Lab.

Followed by a reception with food and drink in 3^rd floor atrium