BI 009 Blake Richards: Deep Learning in the Brain

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 and Brains Program of the Canadian Institute for Advanced Research (CIFAR).
• The paper we discuss:
  • Towards Deep Learning With Segregated Dendrites.
• Code to run the model on Github.
• If you’d rather watch a talk, here’s the same topic in a great talk by Blake.
• The idea of approaching neuroscience from the perspective there are general principles of computation applicable to both brains and AI:
  • Geoffrey Hinton.
  • Cybernetics.
  • McCullough and Pitts artificial neuron: Their original paper and a nice tutorial.
  • Frank Rosenblaut.
  • Demis Hassabis, who founded Deepmind, wrote a great review of how AI and neuroscience can work together.
• Donald Hebb of the famed Hebbian Learning in his famous book The Organization of Behavior: A Neuropsychological Theory.
• Konrad Kording’s 2001 paper articulating the same idea we discuss: Supervised and Unsupervised Learning with Two Sites of Synaptic Integration.
• MNIST dataset of handwritten digits – used to train and test a lot of machine learning networks.
• Eliminative Materialism, the idea our common sense conception of the mind is false.