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	Podcast:		Brain Inspired
	Episode:		BI 009 Blake Richards: Deep Learning in the Brain
	Category:		Science & Medicine
	Duration:		01:11:00
	Publish Date:		2018-09-13 09:59:21
	Description:		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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