Andrew Saxe is a theoretical neuroscientist and is a Sir Henry Dale Fellow and Joint Group Leader at the Gatsby Computational Neuroscience Unit and Sainsbury Wellcome Centre at UCL. His research focuses on developing a mathematical toolkit for analysing and describing phenomena in neuroscience. Currently, he is working on the theory of deep learning, which uses artificial neural network models, and aims to apply this to explain how learning is instantiated in neural networks in the brain.
TIMESTAMPS
(00:38) – Nature of intelligence
(10:23) – Theoretical neuroscience
(11:31) – What attracted Andrew to theoretical neuroscience
(12:16) – Best route to get into theoretical neuroscience
(16:55) – Collaborating with experimental neuroscientists
(25:34) – Artificial vs biological neural networks
(34:06) – What deep learning has taught us about the brain
(37:32) – Linear neural networks
(43:34) – Grand unified theory of neural networks
(45:35) – Incorporating biological aspects into neural networks
(48:53) – Artificial general intelligence
(51:13) – Is maths invented or discovered?
(52:29) – Advice for young scientists
