#222 – Jay McClelland: Neural Networks and the Emergence of Cognition

#222 – Jay McClelland: Neural Networks and the Emergence of Cognition

Jay McClelland is a cognitive scientist at Stanford. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Jay’s Website: https://stanford.edu/~jlmcc/

PODCAST INFO:
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OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(07:12) – Beauty in neural networks
(11:31) – Darwin and evolution
(17:16) – The origin of intelligence
(23:58) – Explorations in cognition
(30:02) – Learning representations by back-propagating errors
(36:27) – Dave Rumelhart and cognitive modeling
(49:30) – Connectionism
(1:12:23) – Geoffrey Hinton
(1:14:19) – Learning in a neural network
(1:31:11) – Mathematics & reality
(1:38:19) – Modeling intelligence
(1:48:57) – Noam Chomsky and linguistic cognition
(2:03:18) – Advice for young people
(2:14:26) – Psychiatry and exploring the mind
(2:27:04) – Legacy
(2:32:53) – Meaning of life

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