| ▲ | hbrn an hour ago | ||||||||||||||||
> work on one specific problem, right? That is the opposite of "general purpose". A business doesn't need Jev for the sake of Jev. Most business are solving specific problems. And fine-tuning got a lot cheaper these days - I've seen claims here on HN that ~500 examples is enough to beat Jev. > "nobody thought it's a good tradeoff", which again is false, there was huge demand for a cheap and accurate general purpose classifier There wasn't. The hope is that there was a latent demand, but we've yet to see if it's truly latent or just manufactured. Noone is saying "hell yeah, finally we got a general purpose classifier, my business needed it so much". The typical message is "this seems cool, let me see where I can apply it". The fact that name itself is a play on Jevons Paradox illustrates that there was no demand until Jev was released. | |||||||||||||||||
| ▲ | baobabKoodaa 27 minutes ago | parent [-] | ||||||||||||||||
Yes, businesses are solving specific problems, but most businesses have more than 1 problem to solve. No, it is not economical to pay a data scientist to develop a custom model for each of your tiny problems. It is often much more economical to use a general purpose solution, like an LLM, or now, Jev. | |||||||||||||||||
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