GPT-4 is still the flagship model "of humanity"; it is still the best model that is publicly available. The intent of the paper is to determine whether the best general model can compete with specialized models - how do you do that without using the best general model?
'Closed source' science happens in every industry. While you may not think of what DOW is doing at science, it is and huge companies like that progress by their internal workings.
What you're stating is something else, that maybe we should fund sciences, such as AI more, but we really did that in the past and it had it's own fits and starts. Then transformers came out of Google and private industry has been leading the way in AI. If you want to keep up with cutting edge and the 10s of millions needed to train them, you'll need to use these private models.
Hackers hack stuff from private companies all the time. Hackers use proprietary software. There is no purity test we have to pass.
I have high hopes that models will end up a bit like Linux servers, where everyone is building on open foundations.
GPT-4 almost disappeared last week. Aside from the obvious AI bus factor and "continuity of science" concerns, I find it absurd that so many papers and open source ML/LLM frameworks and libraries exist that simply would not work at all if not for GPT-4. Have we simply given up?
I thought this was hacker news.