Can't believe how right we were, too.

You seem to be winking a little bit and I’m not sure exactly what you’re trying to say, but I agree with the one you are replying to: the author of this article wrote a lot of words - like a lot a lot of words - only to look very foolish a short time later. And I think much ink was similarly spilled writing very similar piece smirking at people who thought LLMs could do real intellectual work. And they were all wrong.

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JoshTriplett 16 hours ago | parent [-]

It is absolutely the case that some things people wrote about AI and LLMs in the past is no longer true; it's a fast-changing area.

It's also the case that some things remain true. If someone says "don't use them for X because their quality isn't good enough", that's a recommendation with an expiration date. But if someone says "don't use them for X" for any number of other good reasons, that recommendation is often timeless.

"Can it" is changing rapidly. Much more rapidly than "Should it".

	▲	rpdillon 13 hours ago \| parent \| next [-]
		> But if someone says "don't use them for X" for any number of other good reasons, that recommendation is often timeless. Are the good reasons timeless? I guess it's hard to parse what you're saying without some concrete examples. Is there any advice about what to use them for from 2022 or 2023 that you feel is true today, and you expect will be timeless? You said "often", so I'm assuming there are a handful of examples. Ultimately though, this is not an objective discussion, since we're talking about "should", so I'm mainly asking out of curiosity on your view of things. The main example I can think of today is that you shouldn't do professional prose writing with LLMs. Obviously the models have gotten better, but writing is one of those areas where it produces middling output, though even here I hesitate because with a 21% illiteracy rate, it writes better than many adults in the US.
	▲	daishi55 16 hours ago \| parent \| prev [-]
		Can you give an example of some of these things?