[simianwords]

I'm asking for a single example.

[qsera]

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.

[simianwords]

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.

[qsera]

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]

I trust you. If it were happening so frequently you may be able to give me a single prompt to get it to bullshit?

[the_snooze]

I did this in one attempt just now: https://gemini.google.com/share/b4e016be1f69

#8 has an incorrect answer (3 appearances according to Gemini, 2 according to reality https://en.wikipedia.org/wiki/Bowl_championship_series#BCS_a...)

So it works well 95% of the time for literally a trivial use case. Imagine if any other tech tool had that kind of reliability: `ls` displays 95% of your files, your phone successfully sends and receives 95% of text messages, or Microsoft Word saving 95% of the characters you typed in. That's just not acceptable.

[simianwords]

Hi! The challenge was ChatGPT but even then it looks like you used the weakest version of Gemini.