Towards Data Science

96. Jan Leike - AI alignment at OpenAI

22 snips
Sep 29, 2021
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1
Introduction
00:00 • 3min
2
Is There a Career Pathway That You Want to Be On?
02:44 • 2min
3
Scale Ability of Alignment Solutions
04:50 • 2min
4
Is There a Time Line Tour to a G I Development?
06:49 • 3min
5
Are You Hedging Against Specific Risks?
09:27 • 2min
6
Reward Modelling in Reenforcement Learning
11:10 • 5min
7
Recursive Reward Modelling
15:46 • 5min
8
Is the Human Being at the Lower Level of the Recursion?
20:44 • 3min
9
Is There a Misalignment?
24:10 • 2min
10
Is There a Way to Measure Degree of Misalignment?
25:54 • 5min
11
The Balance Between Experimentation and Theory in the Alignment Community?
30:32 • 2min
12
I Don't Think Wire Heading Is That Widely Understandable Outside of an Allignment Research
32:41 • 4min
13
Is There a Scale Gap in Access to Large Models?
36:22 • 3min
14
Scaling Laws for Language Models
39:04 • 4min
15
Gpty 3
43:17 • 2min
16
What's Going on With G Pty Three?
45:38 • 2min
17
Reenforcementing From Human Feedback
47:14 • 2min
18
The Uncanny Valley of Capabilities and Alignment
49:08 • 2min
19
Is There a Competent Approach to Alinemend?
50:54 • 2min
20
Is Machine Learning a Soft Engineering Problem?
52:42 • 2min
21
A G I MVP
54:41 • 2min
22
How Do You Solve a Language Model That Produces a Harmful Output?
56:11 • 2min
23
How to Alline a System or Arbitrarity Powerful
58:27 • 3min
24
Is There Room for Totally Novel Approaches to This?
01:01:35 • 2min
25
Are You Hiring Reset Engineers?
01:03:21 • 2min