Why do all arguments from AI boosters boil down to this same cycle:

A new model is released, AI fans hail it as huge shift in whatever metrics the AI vendor has gamed this time, and all criticism is shrugged off as "not up to date" and met with "try the new model!" Then, once level heads actually put the claims to the test and find it wanting, criticism is met with "you're just not using it right, you have to learn how to prompt/context/loop engineer for best results" until the next model comes out and this argument repeats.

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wseqyrku 3 hours ago | parent | next [-]

> AI fans hail it as huge shift in whatever metrics the AI vendor has gamed this time

Hint: Those are not AI fans. (See the top comment for context.)

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heresalexandria 4 hours ago | parent | prev [-]

It shouldn't be a surprise that the baseline for "best" shifts as better tech comes out, but that doesn't make dated models any less capable than they were when they came out.

Skeptics continue to move the goalposts on what constitutes this mattering, but the fact that frontier systems are making novel maths & sciences discoveries and I can run an LLM on my phone for simple tasks that would've been unthinkable a few years ago are testaments to the directionality of the tech.

	▲	lowsong 4 hours ago \| parent [-]
		Ironically it is you who is most at risk from the direction this is taking. When this house of cards collapses, AI research dries up, and companies pivot to the next hype cycle there will be a generation of people left with atrophied skills and lingering addiction and psychosis. The most flexible will bounce back just fine, but many will never recover from this damage. Sincerely, I hope you're in the former category.