ML papers by Western universities barely touch on the problems that practitioners face.

The only papers I see that are routinely useful have half the authors having a .in or .cn email at the end with the rest having Indian and Chinese names in US institutions.

The only western papers which aren't extended advertisements for their company are from people who are making something for themselves.

For example the best paper on image classification I've ever seen was posted on a private discord and was about better labeling the parts of a vagina as part of a stable diffusion training pipeline.

I used the methods without change and got better than state of the art for document segmentation.

Figuring out new and better ways to make the owners richer is both a real-world and chronically underfunded problem.

> Ah yes, the real world of corporations and all their made-up bullshit.

You're posting that sort of message in a startup-oriented online forum.

There was a point in time where Google was lauded by it's success story as progress originating in investments in academia.