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.
Mentioned in the show Follow Blake on twitter: @tyrell_turing Blake’s Learning in Neural Circuits (LiNC) Laboratory. He’s a Fellow with the Learning in Machines...
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Find out more about Steve at his website. I discovered him when I found his book chapter "What Can AI Get from Neuroscience?" in...
