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.
Daeyeol and I discuss his book Birth of Intelligence: From RNA to Artificial Intelligence, which argues intelligence is a function of and inseparable from...
Jon and I discuss understanding the syntax and semantics of language in our brains. He uses linguistic knowledge at the level of sentence and...
Support the show to get full episodes and join the Discord community. Irina is a faculty member at MILA-Quebec AI Institute and a professor...
