Yeah all the stuff I was seeing seemed to be variations and light wrappers around openai APIs and such. We don't need a million versions of those things, one or two clear 'winners' should emerge. You can see them here, expand it to 50 per page and start browsing down after the usual suspects: https://awesomepython.org/

I'm sorry but I think you don't know what you're looking at - of the NN things in the top 50 there I see 4 such wrappers. The remainder are the NN frameworks and various perf motivated implementations.

Also I don't know how this list is built but it seems to be literally measuring current popular things - so by definition no matter when i visit this list whatever is it at the top will probably wane in population shortly after I've visited.

In a language that has a million incompatible and partial solutions to packaging?

I think this is more comparable to the bajillion JS frameworks that popped up between like 2015 and 2020.

Same kinda deal with the big frameworks either surviving (likely with large rewrites for improvements) or succeeded by a replacement. But it feels like that's died down a bit.

> pytorch, tensorflow, pandas, numpy, scikit-learn

I think it's likely these will either survive or be replaced by a successor - but we wont be seeing 100 new ai packages a day.