>95% is not my experience and frankly dishonest.

Quite frankly, this is exactly like how two people can use the same compression program on two different files and get vastly different compression ratios (because one has a lot of redundancy and the other one has not).

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simianwords 2 hours ago | parent [-]

I'm asking for a single example.

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qsera 2 hours ago | parent [-]

But why do you need an example? Isn't it pretty well understood that LLMS will have trouble responding to stuff that is under represented in the training data?

You will just won't have any clue what that could be.

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simianwords 2 hours ago | parent [-]

fair so it must be easy to give an example? I have ChatGPT open with 5.4-thinking. I'm honestly curious about what you can suggest since I have not been able to get it to bullshit easily.

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qsera 2 hours ago | parent [-]

I am not the OP, an I have only used ChatGPT free version. Last day I asked it something. It answered. Then I asked it to provide sources. Then it provided sources, and also changed its original answer. When I checked the new answers it was wrong, and when I checked sources, it didn't actually contain the information that I asked for, and thus it hallucinated the answers as well as the sources...

	▲	simianwords an hour ago \| parent [-]
		I trust you. If it were happening so frequently you may be able to give me a single prompt to get it to bullshit?