2024-04-07

[public] 248K views, 42.2K likes, dislikes audio only

3Blue1Brown

Demystifying attention, the key mechanism inside transformers and LLMs.

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Special thanks to these supporters: https://www.3blue1brown.com/lessons/attention#thanks

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

Demystifying self-attention, multiple heads, and cross-attention.

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

The first pass for the translated subtitles here is machine-generated, and therefore notably imperfect. To contribute edits or fixes, visit https://translate.3blue1brown.com/

And yes, at 22:00 (and elsewhere), "breaks" is a typo.

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Here are a few other relevant resources

Build a GPT from scratch, by Andrej Karpathy

https://youtu.be/kCc8FmEb1nY

If you want a conceptual understanding of language models from the ground up, @vcubingx just started a short series of videos on the topic:

https://youtu.be/1il-s4mgNdI?si=XaVxj6bsdy3VkgEX

If you're interested in the herculean task of interpreting what these large networks might actually be doing, the Transformer Circuits posts by Anthropic are great. In particular, it was only after reading one of these that I started thinking of the combination of the value and output matrices as being a combined low-rank map from the embedding space to itself, which, at least in my mind, made things much clearer than other sources.

https://transformer-circuits.pub/2021/framework/index.html

Site with exercises related to ML programming and GPTs

https://www.gptandchill.ai/codingproblems

History of language models by Brit Cruise,  @ArtOfTheProblem 

https://youtu.be/OFS90-FX6pg

An early paper on how directions in embedding spaces have meaning:

https://arxiv.org/pdf/1301.3781.pdf

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Timestamps:

0:00 - Recap on embeddings

1:39 - Motivating examples

4:29 - The attention pattern

11:08 - Masking

12:42 - Context size

13:10 - Values

15:44 - Counting parameters

18:21 - Cross-attention

19:19 - Multiple heads

22:16 - The output matrix

23:19 - Going deeper

24:54 - Ending

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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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