Brain Inspired

BI 009 Blake Richards: Deep Learning in the Brain


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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.
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        Brain InspiredBy Paul Middlebrooks

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