In this second part of my discussion with Wolfgang (check out the first part), we talk about spiking neural networks in general, principles of brain computation he finds promising for implementing better network models, and we quickly overview some of his recent work on using these principles to build models with biologically plausible learning mechanisms, a spiking network analog of the well-known LSTM recurrent network, and meta-learning using reservoir computing.
Jörn, Niko and I continue the discussion of mental representation from last episode with Michael Rescorla, then we discuss their review paper, Peeling The...
Support the show to get full episodes and join the Discord community. Hakwan and I discuss many of the topics in his new book,...
David, John, and I discuss the role of complexity science in the study of intelligence. In this first part, we talk about complexity itself,...
