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The bulk of academic work is chasing grants, not "curiosity driven research". If universities want professors not to leave in droves to tech companies that will consistently give them funding and cut away the bullshit that eats up the majority of a professor's time, they should try competing, rather than bemoaning that professors are no longer following the sacred path of academic asceticism.

While I would like to stop chasing grants as much as the next tenure track assistant professor, I don't think it's fair to characterize "the bulk" of academic work as chasing grants.

If anything, it's responding to emails ;)

Emails and sitting in meetings (e.g. https://twitter.com/research_tim/status/1017506139137826819 ).

I do not think this is what the piece is arguing. Rather, the concern is that by creating these 80/20 splits, the core values of the university are compromised. There's nothing a priori wrong with industrial research, it's this attempted hybrid that's problematic. Hence the title, "you cannot serve two masters".

Quoting the piece, "Part of the point of being a big company is to control your environment by crushing, containing, or co-opting inconvenient innovations." I think the author is arguing that attitude is fundamentally at odds with the values of the academy.

If BigCompany expects its research center to crush inconvenient innovations, they're not really running a research center, they're just calling it that because they like the titles.

i read "inconvenient" as "competing". if your r&d can lead to a few choice patents (or you "just" buy them) you can sometimes hamstring competition or get little graft by leeching off competitor's developments.

The point of being a big company, not the point of running a research center.

Top conferences accept papers with a large expected impact, not necessarily papers the authors were really curious about. It's deeper than merely what time is spent on, it's also where accolades are given. The facebook thing shows real problems to the researchers and provides good data, good starts to high impact papers.

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