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by namaria
403 days ago
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In the very narrow fields where I have a deep understanding, LLM output is mostly garbage. It sounds plausible but doesn't stand up to scrutiny. The basics that it can regurgitate from wikipedia sound mostly fine but they are already subtly wrong as soon as they depart from stating very basic facts. Thus I have to assume that for any topic I do not fully understand - which is the vast majority of human knowledge - it is worse than useless, it is actively misleading. I try to not even read much of what LLMs produce. I might give it some text and riff about it if I need ideas, but LLMs are categorically the wrong tool for factual content. |
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Why do you have to make that assumption? An expert arborist likely won’t know much about tuning GC parameters for the JVM but that won’t make them “worse than useless” or “actively misleading” when discussing other topics, and especially not when it comes to the stuff that’s relatively tangential to their domain.
I think the difference we have is that I don’t expect the models to be experts in any domain nor do I expect them to always provide factual content; the library can provide factual content—if you know how to use it right.