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Comment by Joel_Mckay

3 hours ago

It was actually a trivial allusion to a rather old poetic parable, and highlights a foundational flaw in LLM inference model statistical salience.

If a LLM based chat bot does ever answer it correctly, than you know with a fair degree of certainty it was content moderators stepping into the chat. Have a wonderful day. =3

https://en.wikisource.org/wiki/The_Poems_of_John_Godfrey_Sax...

https://en.wikipedia.org/wiki/Blind_men_and_an_elephant

OK, I still have no idea what you actually think the "correct" answer is.

  • I think they want the correct answer to be "your question doesn't really make sense, so I'm not going to answer it". (But I also think Opus's answer is better.)

    • All the answers I've seen so far are assuredly not inaccurate (the elephants trunk is like a snake), but never fully correct (an elephant is not a snake).

      While the LLM spits out each ambiguous context search result, it never answers the actual query without a human cheaters help. =3

      https://en.wikipedia.org/wiki/Pareidolia