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by roadside_picnic
4 hours ago
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> It's like the infinite monkeys on typewrighters that will type whatever you are looking for, given infinite time. In the monkey example the infinite time is doing a lot of work there. The fact that LLMs can search through semantic space and find reasonably correct paths in a reasonable time is directly tied to the reason why they are valuable. Saying "these two things are similar except one can be useful and one can't" is not a great comparison. For me the real lesson learned isn't how "smart" LLMs are, but rather how much human work is basically reducible to repeating past work with minor variation. Human's believe they are "reasoning" but so much code writen is just the human brain doing the same autocomplete style work that LLMs can do now. |
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This seems like a reasonable view to me. It's surprising just how much better priors matter and how we can develop those priors by training on a bunch of text. But it also explains, or at least hints at an explanation, for why LLM capabilities are so jagged, and in such inhuman ways.