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.
Thomas and I talk about what happens in the brain’s visual system when you see something versus imagine it. He uses generative encoding and...
Support the show to get full episodes and join the Discord community. Jolande Fooken is a post-postdoctoral researcher interested in how we move our...
Support the show to get full episodes and join the Discord community. Check out my free video series about what's missing in AI and...
