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.
Support the show to get full episodes and join the Discord community. Doris, Tony, and Blake are the organizers for this year’s NAISys conference,...
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...
Kyle and I talk about his work modeling the basal ganglia and its circuitry to control whether we take an action and how we...
