Generally Intelligent

Episode 18: Oleh Rybkin, UPenn, on exploration and planning with world models

34 snips
Jul 11, 2022
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Episode notes
1
Introduction
00:00 • 5min
2
How Did You Get Into Your Pagete?
05:01 • 4min
3
Nour Science and the Architecture of the Brain
08:57 • 4min
4
I've Been Thinking About Reason
13:24 • 5min
5
Is There a Big Transformer in the Learning Process?
18:12 • 4min
6
How to Adapt to New Situations?
22:19 • 3min
7
Do You Have Intuition on How to Get Quick Adoption to New Situations?
24:55 • 1min
8
Morals Enable Latent Learning
26:13 • 6min
9
Plan to Explore
31:45 • 5min
10
The Best Way to Measure Uncertainty Estimation
36:18 • 2min
11
The Old Radio Isn't Working, Is It?
37:59 • 5min
12
Theorems of Theoeo Fasti
43:24 • 4min
13
How to Define Scales?
47:22 • 2min
14
Using a Robotic Agent
49:37 • 3min
15
The Agent With Four Legs
52:46 • 3min
16
The Right Way to Specify Goals
55:18 • 3min
17
How Do We Learn Language Conditional Agents?
58:25 • 2min
18
The Problem Is Learning From the Internet
01:00:37 • 2min
19
Is There an Alternative to Generalization in Reenforcement Learning?
01:02:59 • 4min
20
I Don't Understand Tiktok, I Don't Understand Tick Talk.
01:06:42 • 3min
21
Is There a Need for Better Generalization?
01:10:04 • 4min
22
How to Train a Moral and Image Nit for a Big Data Set
01:13:45 • 5min
23
How to Train a Dynamic Model on Utope?
01:19:06 • 3min
24
The Structure People Have Lost to the Giant Transformers in Conpee Mission
01:22:12 • 6min
25
Morals Are Important, Right?
01:27:54 • 4min
26
Is There a Benchmark for Adapting to a New Situation?
01:32:02 • 4min
27
Train Robert to Open a Cabinet in the Google Kitchen
01:35:52 • 3min
28
How to Train a Biped Robbert to Walk in Simulation
01:39:12 • 4min
29
The Future of Robotic Manipulation
01:43:19 • 5min
30
How to Come Up With a Good Idea
01:48:33 • 3min
31
The Way People Fail to Write Good Papers
01:51:08 • 3min
32
Did a Lot of Things Work?
01:54:26 • 4min
33
Plant Explore Does Work, but It's Still Too Simple of a Result
01:58:14 • 3min