2024-08-31

[public] 134K views, 26.5K likes, dislikes audio only

3Blue1Brown

Unpacking the multilayer perceptrons in a transformer, and how they may store facts

Instead of sponsored ad reads, these lessons are funded directly by viewers: https://3b1b.co/support

An equally valuable form of support is to share the videos.

AI Alignment forum post from the Deepmind researchers referenced at the video's start:

https://www.alignmentforum.org/posts/iGuwZTHWb6DFY3sKB/fact-finding-attempting-to-reverse-engineer-factual-recall

Anthropic posts about superposition referenced near the end:

https://transformer-circuits.pub/2022/toy_model/index.html

https://transformer-circuits.pub/2023/monosemantic-features

Some added resources for those interested in learning more about mechanistic interpretability, offered by Neel Nanda

Mechanistic interpretability paper reading list

https://www.alignmentforum.org/posts/NfFST5Mio7BCAQHPA/an-extremely-opinionated-annotated-list-of-my-favourite

Getting started in mechanistic interpretability

https://www.neelnanda.io/mechanistic-interpretability/getting-started

An interactive demo of sparse autoencoders (made by Neuronpedia)

https://www.neuronpedia.org/gemma-scope#main

Coding tutorials for mechanistic interpretability (made by ARENA)

https://arena3-chapter1-transformer-interp.streamlit.app/

Sections:

0:00 - Where facts in LLMs live

2:15 - Quick refresher on transformers

4:39 - Assumptions for our toy example

6:07 - Inside a multilayer perceptron

15:38 - Counting parameters

17:04 - Superposition

21:37 - Up next

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These animations are largely made using a custom Python library, manim. See the FAQ comments here:

https://3b1b.co/faq#manim

https://github.com/3b1b/manim

https://github.com/ManimCommunity/manim/

All code for specific videos is visible here:

https://github.com/3b1b/videos/

The music is by Vincent Rubinetti.

https://www.vincentrubinetti.com

https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown

https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u

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