DiscoverAXRP - the AI X-risk Research Podcast36 - Adam Shai and Paul Riechers on Computational Mechanics
36 - Adam Shai and Paul Riechers on Computational Mechanics

36 - Adam Shai and Paul Riechers on Computational Mechanics

Update: 2024-09-29
Share

Description

Sometimes, people talk about transformers as having "world models" as a result of being trained to predict text data on the internet. But what does this even mean? In this episode, I talk with Adam Shai and Paul Riechers about their work applying computational mechanics, a sub-field of physics studying how to predict random processes, to neural networks.

Patreon: https://www.patreon.com/axrpodcast

Ko-fi: https://ko-fi.com/axrpodcast

The transcript: https://axrp.net/episode/2024/09/29/episode-36-adam-shai-paul-riechers-computational-mechanics.html

 

Topics we discuss, and timestamps:

0:00:42 - What computational mechanics is

0:29:49 - Computational mechanics vs other approaches

0:36:16 - What world models are

0:48:41 - Fractals

0:57:43 - How the fractals are formed

1:09:55 - Scaling computational mechanics for transformers

1:21:52 - How Adam and Paul found computational mechanics

1:36:16 - Computational mechanics for AI safety

1:46:05 - Following Adam and Paul's research

 

Simplex AI Safety: https://www.simplexaisafety.com/

 

Research we discuss:

Transformers represent belief state geometry in their residual stream: https://arxiv.org/abs/2405.15943

Transformers represent belief state geometry in their residual stream [LessWrong post]: https://www.lesswrong.com/posts/gTZ2SxesbHckJ3CkF/transformers-represent-belief-state-geometry-in-their

Why Would Belief-States Have A Fractal Structure, And Why Would That Matter For Interpretability? An Explainer: https://www.lesswrong.com/posts/mBw7nc4ipdyeeEpWs/why-would-belief-states-have-a-fractal-structure-and-why

 

Episode art by Hamish Doodles: hamishdoodles.com

Comments 
00:00
00:00
x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

Sleep Timer

Off

End of Episode

5 Minutes

10 Minutes

15 Minutes

30 Minutes

45 Minutes

60 Minutes

120 Minutes

36 - Adam Shai and Paul Riechers on Computational Mechanics

36 - Adam Shai and Paul Riechers on Computational Mechanics