Jay McClelland is a pioneer in the field of artificial intelligence and is a cognitive psychologist and professor at Stanford University in the psychology, linguistics, and computer science departments. Together with David Rumelhart, Jay published the two volume work Parallel Distributed Processing, which has led to the flourishing of the connectionist approach to understanding cognition.

In this conversation, Jay gives us a crash course in how neurons and biological brains work. This sets the stage for how psychologists such as Jay, David Rumelhart, and Geoffrey Hinton historically approached the development of models of cognition and ultimately artificial intelligence. We also discuss alternative approaches to neural computation such as symbolic and neuroscientific ones.

Patreon (bonus materials + video chat):

• 00:00 : Preview

Part II. The Brain

• 00:20:20 : Structure of neurons

Part III. Approaches to AI, PDP, and Learning Rules

• 01:12:35 : Chomsky, symbolic rules, universal grammar

Further reading:

Rumelhart, McClelland. Parallel Distributed Processing.

McClelland, J. L. (2013). Integrating probabilistic models of perception and interactive neural networks: A historical and tutorial review

Twitter: @iamtimnguyen

Webpage: http://www.timothynguyen.org