Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neural networks overfit data when they can, and how evolution works the same way on a much slower timescale.
Show notes:
What is creativity? How do we measure it? How do our brains implement it, and how might AI?Those are some of the questions John,...
BI NMA 04: Deep Learning Basics Panel This is the 4th in a series of panel discussions in collaboration with Neuromatch Academy, the online...
Michael and I discuss the philosophy and a bit of history of mental representation including the computational theory of mind and the language of...
