In this episode of “Brain Inspired,” Paul Middlebrooks talks with Tomaso Poggio, director of the Center for Biological and Computational Learning and the Center for Brains, Minds, and Machines, both at the Massachusetts Institute of Technology. Poggio has for decades, in collaboration with many prominent figures across cognitive science and physics, sought theories to explain fundamental learning abilities of brains and machines. He explains a few of those principles, such as compositional sparsity—the idea that many simple functions connected in hierarchies can perform complex functions. More broadly, Poggio reflects on the past, present and future of the science of intelligence.
