

124 - Jay McClelland: Deep Learning, Neural Networks, and Artificial Intelligence
Aug 6, 2023
Chapters
Transcript
Episode notes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
Introduction
00:00 • 3min
Why I Chose a Career in Psychology to Pursue My Research Interests
03:19 • 5min
Parallel Distributed Processing Explains Cognitive Function
08:08 • 4min
The Perception of Letters in Words
12:24 • 3min
The Neural Network's Ability to Recognize Letters
15:02 • 5min
The Conspiracy of Mental Agents
19:39 • 2min
The Connectionist Model of Parallel Distributed Processing
21:35 • 2min
The Bidirectionality and Mutuality of Cognitive Networks
23:06 • 2min
The Cognitive Phenomenon of Learning
25:01 • 1min
How to Teach a Neural Network to Complete a Pattern Like a Word
26:19 • 5min
The Motivation Behind the Interactive Activation Model
31:04 • 5min
The Importance of Parallel Distributed Processing in Intelligence
36:34 • 2min
The Photo and Pollution Argument for the Parallel Distributed Processing Model Never Capturing Human Intelligence
38:07 • 6min
The Importance of Exploiting Context Effectively
44:00 • 3min
The Origins of AI in Psychology
47:00 • 4min
The Limits of Affective Reasoning
51:25 • 5min
How Artificial Neural Networks Capture Advanced Human Cognitive Ability
56:33 • 6min
The Importance of Goal-Directedness
01:02:11 • 4min
The Future of Artificial Intelligence
01:06:32 • 4min
The Importance of Perforation in Science
01:10:41 • 2min
The Importance of Intention
01:13:04 • 2min
The Power of Neural Networks for Providing Insight
01:14:56 • 5min
The Importance of the Macro Structure of the Neural Network
01:19:26 • 5min
The Transformer Based Revolution in Language Models
01:24:12 • 2min
The Power of the Transformer
01:25:59 • 3min
The Importance of Context in Translation
01:29:05 • 4min
Consolidation: A New Principle for Reasoning
01:33:03 • 2min
CHATG-EPT's Knowledge in Weights
01:35:26 • 2min
How to Use a Word in a Sentence
01:37:22 • 5min
The Emergence of a Connectionist Model
01:42:18 • 2min
The Gap Between Neural Networks and Our Pioneering Scientists
01:44:13 • 4min