Honestly, is there a big difference anymore? The vast majority of papers I read are either by industry directly or have industry as a partner (as an author, not just acknowledgements). There are of course some, and even plenty of examples, but it does seem industry partners is almost necessary these days. I'm not convinced that level of interaction is healthy, for either parties.
Only a very small subset of industry cares about academic publishing, and even within that subset it's only a fraction of groups at a fraction of corps that consider publishing a primary or even secondary objective.
The groups that do care about those things can be good gigs, but are generally not the place in the company you want to be anyways, unless you can get in and out (for good) in <10 years. If you can do something that actually impacts the business -- that is actually useful to other humans -- no one gives a shit about h-indices or kaggle scores. And you'll be better compensated anyways.
You're measuring the wrong direction. Don't measure what percentage of industry publishes with academics. Instead, measure what percent of academics __in ML__ publish with industry. This direction because one is much larger than the other. Second, I mean... I am a researcher... and I'm talking about the environment I'm working in. It sounds like you're outside this environment trying to educate me on it. Am I misunderstanding here?
> can do something that actually impacts the business -- that is actually useful to other humans
Do not confuse these two. That's incredibly naive.
>
Honestly, is there a big difference anymore? The vast majority of papers I read are either by industry directly or have industry as a partner (as an author, not just acknowledgements).
Read more pure math papers, then you will see the difference. :-)
I thought we were talking ML here. I mean you're not wrong (I do do this) but context. But in ML, well... I mean even Max Welling is connected with Microsoft.
This is no contradiction: there exist quite pure math papers whose content is very relevant for the mathematics behand ML algorithms. :-)
I do have the impression that the kind of research in ML that is not strongly associated with the recent "machine-learning industrial complex" by now tends to become published in another subject area.
Sure, I agree with you. I just wouldn't refer to that work as pure math. And let's be real, most people are not working on the theoretical side of ML. Realistically people are anti theory in the ML space and it's really weird to me because it's a self fulfilling prophecy and the complaints are "it's not very good because not a lot of community effort hasn't been put in so let's not waste our time"