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this post was submitted on 23 Sep 2024
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It’s frustrating that the article deals treats the problem like the mistake was including Martin’s name in the data set, and muses that that part isn’t fixable.
Martin’s name is a natural feature of the data set, but when they should be taking about fixing the AI model to stop hallucinations or allow humans to correct them, it seems the only fix is to censor the incorrect AI response, which gives the implication that it was saying something true but salacious.
Most of these problems would go away if AI vendors exposed the reasoning chain instead of treating their bugs as trade secrets.
Or just stop using buggy AIs for everything.
just shows that these "ai"'s are completely useless at what they are trained for
They're trained for generating text, not factual accuracy. And they're very good at it.
Do LLMs actually have a reasoning chain that would be comprehensible to users?
https://learnprompting.org/docs/intermediate/chain_of_thought
It's suspected to be one of the reasons why Claude and OpenAI's new o1 model is so good at reasoning compared to other llm's.
It can sometimes notice hallucinations and adjust itself, but there's also been examples where the CoT reasoning itself introduce hallucinations and makes it throw away correct answers. So it's not perfect. Overall a big improvement though.