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Published · transcript-backed

Sholto Douglas: belief

28 Mar 2024 Dwarkesh Podcast Sholto Douglas & Trenton Bricken — How LLMs actually think

“I think the original chain-of-thought paper had that as almost an immersion property of the model.”

— Sholto Douglas

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Speaker
Sholto Douglas
Attribution
Verified speaker
Claim type
belief
Recorded
28 Mar 2024
Publisher
Dwarkesh Podcast

Transcript context

…Is the claim that when you fine-tune on chain-of-thought, the key and value weights change so that the sort of steganography can happen in the KV cache? I don't think I could make that strong a claim there, but that's a good headcanon for why it works. I don't know if there are any papers explicitly demonstrating that or anything like that. But that's at least one way that you can imagine the model. During pre-training, the model's trying to predict these future tokens and one thing that you can imagine it doing is that it’s learning to smush information about potential futures into the keys and values that it might want to use in order to predict future information. It kind of smooths that information across time and the pre-training thing. So I don't know if people are particularly training on chains-of-thought. I think the original chain-of-thought paper had that as almost an immersion property of the model. You could prompt it to do this kind of stuff and it still worked pretty well. So it’s a good headcanon for why that works. To be overly pedantic here, the tokens that you actually see in the chain-of-thought do not necessarily at all need to correspond to the vector representation that the model gets to see when it's deciding to attend back to those tokens.…

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