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An LLM is a lossy encyclopedia

(simonwillison.net)
509 points tosh | 2 comments | | HN request time: 0s | source

(the referenced HN thread starts at https://news.ycombinator.com/item?id=45060519)
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kgeist ◴[] No.45101806[source]
I think an LLM can be used as a kind of lossy encyclopedia, but equating it directly to one isn't entirely accurate. The human mind is also, in a sense, a lossy encyclopedia.

I prefer to think of LLMs as lossy predictors. If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordingly and survive.

In the real world, with countless fuzzy factors, no predictor can ever be perfectly lossless. The only real difference, for me, is that LLMs are lossier predictors than human minds (for now). That's all there is to it.

Whatever analogy you use, it comes down to the realization that there's always some lossiness involved, whether you frame it as an encyclopedia or not.

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jbstack ◴[] No.45102030[source]
Are LLMs really lossier than humans? I think it depends on the context. Given any particular example, LLMs might hallucinate more and a human might do a better job at accuracy. But overall LLMs will remember far more things than a human. Ask a human to reproduce what they read in a book last year and there's a good chance you'll get either absolutely nothing or just a vague idea of what the book was about - in this context they can be up to 100% lossy. The difference here is that human memory decays over time while a LLM's memory is hardwired.
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withinboredom ◴[] No.45102578[source]
That's not exactly true. Every time you start a new conversation; you get a new LLM for all intents. Asking an LLM about an unrelated topic towards the end of a ~500 page conversation will get you vastly different results than at the beginning. If we could get to multi-thousand page contexts, it would probably be less accurate than a human, tbh.
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1. jbstack ◴[] No.45102827[source]
Yes, I should have clarified that I was referring to memory of training data, not of conversations.
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2. withinboredom ◴[] No.45120236[source]
Training data also deteriorates quite quickly as the context gets longer.