Joel Lehman, OpenAI: Evolution, open-endedness, and reinforcement learning

1

Introduction

00:00 • 2min

2

How Did You Get Into Programming?

02:05 • 5min

3

Novelty Search

06:59 • 5min

4

Machine Learning

12:04 • 3min

5

Open End Machine Learning - What Do You Mean?

14:57 • 4min

6

Random Drippet and Exploration

19:21 • 2min

7

The Difference Between Drift and Exploration in Cue Learning

21:02 • 6min

8

Open Handledness

26:56 • 5min

9

G I

31:58 • 1min

10

The Evolutionary Approach to a G I

33:14 • 3min

11

What Is the Architecture Search Application to Machine Learning?

36:31 • 5min

12

How Did You Get to This False Hocort Insit?

41:56 • 2min

13

The Value of Play in Deep Learning

43:42 • 5min

14

Architecture Search

48:17 • 2min

15

Beyond Open Eadedness, Quantifying Impressiveness

50:40 • 4min

16

The Bustiket Theory of Genius

54:41 • 3min

17

What Influenced You?

57:13 • 5min

18

How to Stay Motivated in Research?

01:02:18 • 2min

19

Are You Taking Care of Yourself?

01:03:58 • 5min

20

What Makes Life's Meaning Fall?

01:09:04 • 2min

21

Taking Risks in a Measured Way

01:10:43 • 2min

22

The Cardinal Sin of a Senior Researcher

01:13:07 • 5min