In this case it found generic advice and was confusing itself.

That's one explanation.

Another could be that it simply has no real *understanding* of anything. It simply did a statistical comparison of the question to the available advice and picked the best match --- kinda what a search engine might do.

Expecting *understanding* from a synthetic, statistical process will often end in disappointment.

Yup. It’s time for us to just accept that LLMs are “similar in meaning” machines not “thinking/ understanding” machines

If you think about it --- an LLM that could really *grasp* "pickleball" from a text description without ever seeing, playing or "experiencing" the game is not just human level intelligence --- it's superhuman.

And the same applies to a lot of real world situations.