The Jim Rutt Show

EP 192 David Krakauer on Science, Complexity and AI

25 snips
Jul 18, 2023
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Episode notes
1
Introduction
00:00 • 2min
2
The Bifurcation of Theory and Data
02:22 • 4min
3
The Origins of Neural Networks
06:21 • 3min
4
The History of Neural Nets
09:31 • 2min
5
The Importance of Regularities in Complex Domains
11:53 • 3min
6
The Uncanny Valley of Complexity
15:12 • 2min
7
The Pros and Cons of Adaptive Computation
17:18 • 2min
8
The Concilience of Traditional Linguists and Language Understanding
19:45 • 2min
9
The Poverty of the Stimulus
21:33 • 4min
10
How to Use Deep Neural Networks for Parsimonious Science
25:38 • 3min
11
The Importance of Symbolic Regression in Astronomy
28:26 • 2min
12
The New Way of Doing Science
30:31 • 2min
13
The Importance of Knowledge in Model Building
32:12 • 2min
14
The Cognitive Synergy of Deep Learning
34:23 • 2min
15
The Evolution of Human Intelligence
36:37 • 3min
16
The Importance of Complexity in Games
39:18 • 2min
17
The Power of Neural Nets in Complexity Science
41:35 • 2min
18
The History of Science and Technology
43:47 • 3min
19
The Importance of Constructs in Economics
46:45 • 2min
20
The Complexity of Adaptive History
48:36 • 2min
21
The Importance of Structure in Neural Nets
51:05 • 3min
22
The Importance of Creativity in the Movie Writing Process
54:26 • 5min
23
The Importance of Bandwidth Limitations in Scientific Revolutions
59:23 • 2min
24
The Polyannas of Machine Learning
01:00:56 • 2min
25
The Importance of Intelligence
01:02:59 • 4min
26
Darwin's Dangerous Idea
01:07:15 • 2min
27
The Paradox of Meta-Oaken
01:09:16 • 3min
28
The Paradox of Evolutionary Time
01:12:40 • 2min
29
Complexity Science and Physical Theory Substitute Parsimony
01:14:35 • 2min
30
The Existential Risk of Models
01:16:08 • 4min
31
The Risks of Narrow AI
01:19:47 • 2min
32
The History of Genetic Engineering
01:22:16 • 2min
33
The Future of Technology
01:24:01 • 6min
34
The Future of Social Media
01:29:40 • 2min
35
The Problem With Outsourcing Human Judgment
01:32:04 • 3min