This feels like an xkcd 169 situation, to be honest.
replyIt was actually a trivial allusion to a rather old poetic parable, and highlights a foundational flaw in LLM inference model statistical salience.
replyIf 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...
OK, I still have no idea what you actually think the "correct" answer is.
replyI 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.)
replyAll 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).
replyWhile the LLM spits out each ambiguous context search result, it never answers the actual query without a human cheaters help. =3
How do you know the fish is playing? Is he happy, enjoying it? =3
replyI agree, part of the ambiguity is also unfairly projecting our own subjective experience onto hapless creatures. =3
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