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.
Announcement: I'm releasing my Neuro-AI course April 10-13, after which it will be closed for some time. Learn more here. Support the show to...
Steve and I discuss his long and productive career as a theoretical neuroscientist. We cover his tried and true method of taking a large...
Support the show to get full episodes and join the Discord community. David runs his lab at UCLA where he's also a distinguished professor. ...
