The Gradient: Perspectives on AI Melanie Mitchell: Abstraction and Analogy in AI
69 snips
Dec 15, 2022 Chapters
Transcript
Episode notes
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Introduction
00:00 • 2min
How Did You Get Into AI?
01:54 • 2min
How Does Not Having a Computer Science Background Influence Your AI Research?
03:55 • 2min
Is There a Difference Between Symbolic AI and Machine Learning?
05:48 • 2min
Is Scaling the Next Big Step in AI Progress?
08:10 • 2min
How Do We Evaluate Language Models?
10:02 • 3min
The Chinese Room and the Zombies
12:32 • 2min
Why AI Is Harder Than We Think?
14:21 • 5min
Is There a Difference Between Human and Computer?
19:25 • 3min
Do You Want to Replicate Human-Like Intelligence?
22:20 • 2min
What Is Intelligence?
24:30 • 2min
Is There a Degree of Intelligence?
26:46 • 2min
Is It Even Useful to Slap That Label on Intelligence?
28:32 • 2min
Is There a Need for Scaling in Artificial Intelligence?
30:38 • 2min
Is There a Causality in the Text to Image Systems?
32:59 • 2min
Analogy and Machine Learning
34:49 • 3min
A Concept Is Something Much Richer Than a Category
38:09 • 2min
Is There a Place That Bottoms Out?
40:21 • 3min
Is There a Bottoming Out in the Physical?
43:09 • 2min
Copycat Architecture - What Is It?
45:11 • 3min
Neural Networks and Symbolic AI
48:25 • 2min
What Advice Would You Give to Someone Starting Out in AI?
50:49 • 4min