124 - Jay McClelland: Deep Learning, Neural Networks, and Artificial Intelligence

124 - Jay McClelland: Deep Learning, Neural Networks, and Artificial Intelligence

Jay McClelland is Lucie Stern Professor in the Department of Psychology at Stanford University, where he is also Director of the Center for Mind, Brain, Computation and Technology. Along with other towering figures like Geoffrey Hinton, Jay is considered one of the fathers of artificial intelligence. In this episode, Robinson and Jay discuss some of his main interests in and contributions to the field, including his work on parallel distributed processing with David Rumelhart, the relationship between neural networks and the brain, and just what developments are necessary for artificial intelligence to replicate the thinking of the greatest human scientists and engineers.


Parallel Distributed Processing: https://a.co/d/aELzYx2


OUTLINE

00:00 In This Episode…

00:30 Introduction

02:55 Jay’s Beginnings in Psychology

07:46 What Is Parallel Distributed Processing?

24:21 Cognitive Phenomena and Neural Networks

37:27 Fodor and Pylyshyn on Neural Networks

52:10 Affective Reasoning

55:52 Advancing AI to Compete with Scientists

01:10:02 What Distinguishes AI From Our Greatest Thinkers?

01:14:15 AI and Mathematical Cognition

01:18:47 Macrostructure and Microstructure

01:43:32 Final Thoughts

Robinson’s Website: http://robinsonerhardt.com


Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.

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