#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: - Paperspace: https://gradient.run/lex to get $15 credit - Skiff: https://skiff.org/lex to get early access
Jay McClelland is a cognitive scientist at Stanford. Please support this podcast by checking out our sponsors:
–
Paperspace
:
https://gradient.run/lex
to get $15 credit
–
Skiff
:
https://skiff.org/lex
to get early access
–
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https://uprisingfood.com/lex
to get $10 off 1st starter bundle
–
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https://foursigmatic.com/lex
and use code LexPod to get up to 60% off
–
Onnit
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https://lexfridman.com/onnit
to get up to 10% off
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