In this first part of our conversation (here's the second part), Wolfgang and I discuss the state of theoretical and computational neuroscience, and how experimental results in neuroscience should guide theories and models to understand and explain how brains compute. We also discuss brain-machine interfaces, neuromorphics, and more. In the next part (here), we discuss principles of brain processing to inform and constrain theories of computations, and we briefly talk about some of his most recent work making spiking neural networks that incorporate some of these brain processing principles.
Show notes: His new book, The Deep Learning Revolution: His Computational Neurobiology Laboratory at the Salk Institute. His faculty page at UCSD. His first...
Steve and I discuss many topics from his new book Know Thyself: The Science of Self-Awareness. The book covers the full range of what...
Support the Podcast Andrew and I discuss his work exploring how various facets of deep networks contribute to their function, i.e. deep network theory....