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.
In this first part of our discussion, Brad and I discuss the state of neuromorphics and its relation to neuroscience and artificial intelligence. He...
Thomas and I discuss the role of recurrence in visual cognition: how brains somehow excel with so few “layers” compared to deep nets, how...
Support the show to get full episodes and join the Discord community. Patryk and I discuss his wide-ranging background working in both the neuroscience...
