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One could say, for instance… A pattern matching algorithm detects when patterns match.
by devmor 1y ago
One could say, for instance… A pattern matching algorithm detects when patterns match.
- 0xDEAFBEAD 1y agoThat's not what's going on here? The algorithms aren't being given any pattern of "being evaluated" / "not being evaluated", as far as I can tell. They're doing it zero-shot. Put it another way: Why is this distinction important? We use the word "knowing" with humans. But one could also argue that humans are pattern-matchers! Why, specifically, wouldn't "knowing" apply to LLMs? What are the minimal changes one could make to existing LLM systems such that you'd be happy if the word "knowing" was applied to them?
- devmor 1y agoNot to be snarky but “as far as I can tell” is the rub isn’t it? LLMs are better at matching patterns than we are in some cases. That’s why we made them! > But one could also argue that humans are pattern-matchers! No, one could not unless they were being disingenuous.
- mewpmewp2 1y agoWhat about animals knowing? E.g. dog knows how to X or its name. Are these things fine to say?
- 0xDEAFBEAD 1y ago>Not to be snarky but “as far as I can tell” is the rub isn’t it? From skimming the paper, I don't believe they're doing in-context learning, which would be the obvious interpretation of "pattern matching". That's what I meant to communicate. >No, one could not unless they were being disingenuous. I think it is just about as disingenuous as labeling LLMs as pattern-matchers. I don't see why you would consider the one claim to be disingenuous, but not the other.