prometheus1992 an hour ago

maybe you entered the AI space during the vibecoding era but there had been ton of useful models before that. especially zero shot models- both for text and images.

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baobabKoodaa 42 minutes ago | parent [-]

Everything you said here is false. No, I didn't enter the AI space during the vibe coding era. I was training custom ML models back in 2017. And no, there haven't been models comparable to Jev before Jev was published.

Jev is:

- accurate

- general purpose

- fast and cheap

Models we had before Jev had at most 2/3 of above qualities, but none of them were 3/3.

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hbrn 24 minutes ago | parent [-]

> Models we had before Jev had at most 2/3 of above qualities, but none of them were 3/3.

You're the one being deceptive here. Jev is trading accuracy, speed, and cost for generality. It's less accurate, slower and more expensive than trained classifiers. So it's still 2 out of 3, but with decimals. Maybe 2.2 out of 3 if I'm being charitable.

And the reason we didn't have that before is because nobody thought it's a good tradeoff.

	▲	baobabKoodaa 8 minutes ago \| parent [-]
		When you say "trained classifiers", you are referring to models which are trained (or fine tuned) to work on one specific problem, right? That is the opposite of "general purpose". Would Jev be more accurate in a specific task if it had been developed only for that task, as opposed to general purpose? Of course it would. So, sure, Jev is trading accuracy for generality. According to you "nobody thought it's a good tradeoff", which again is false, there was huge demand for a cheap and accurate general purpose classifier.