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:
Megan and I discuss her work using metacognition as a way to study subjective awareness, or confidence. We talk about using computational and neural...
Show notes: This is the first in a series of episodes where I interview keynote speakers at the upcoming Cognitive Computational Neuroscience conference in...
Alison and I discuss her work to accelerate learning and thus improve AI by studying how children learn, as Alan Turing suggested in his...
