None of it is correct because it was not asked about Marathon Valley, it was asked about Marathon Crater, a thing that does not exist, and it is claiming that it exists and making up facts about it.

Or it's assuming you are asking about Marathon Valley, which is very reasonable given the context.

Ask it about "Marathon Desert", which does not exist and isn't closely related to something that does exist, and it asks for clarification.

I'm not here to say LLMs are oracles of knowledge, but I think the need to carefully craft specific "gotcha" questions in order to generate wrong answers is a pretty compelling case in the opposite direction. Like the childhood joke of "Whats up?"..."No, you dummy! The sky is!"

Straightforward questions with straight wrong answers are far more interesting. I don't many people ask LLMs trick questions all day.

If someone asked me or my kid "What do you know about Mt. Olampus." we wouldn't reply: "Oh, Mt. Olampus is a big mountain in greek myth...". We'd say "Wait, did you mean Mt. Olympus?"

It doesn't "assume" anything, because it can't assume, that's now the machine works.

> None of it is correct because it was not asked about Marathon Valley, it was asked about Marathon Crater, a thing that does not exist, and it is claiming that it exists and making up facts about it.

The Marathon Valley _is_ part of a massive impact crater.

If you asked me for all the details of a Honda Civic and I gave you details about a Honda Odyssey you would not say I was correct in any way. You would say I was wrong.

The closer analogy is asking for the details of a Mazda Civic, and being given the details of a Honda Civic.

AKA wrong.

Or doing the best with bad question ;)

If I said "Hey what's 0/5" answering "0" because the machine thinks I mean to type "10" is making the worst!

I was using "bullshit" in the Technical Sense™, i.e. _indifferent to the truth of the output_.

[ChatGPT is bullshit ]: https://link.springer.com/article/10.1007/s10676-024-09775-5