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Re:AlphaFold: a solution to a 50-year-old grand challenge in... by softwaredoug on Tuesday December 01, 2020 @03:19PM (#25269393)
Specifically the linked article wonders about the research environment of academia compared to industry. Why teams of hundreds in academia with their own super computing resources couldn’t make the same advances. He posits there’s something not great going on about how academic research environments make advances, the poor incentive structures, the abuse and burnout of PhDs, the lack of open sharing of findings, the obsession with publication quantity over quality...

There’s a reason these PhDs at Google mind aren’t in academia after all doing the same work

Re:AlphaFold: a solution to a 50-year-old grand challenge in... by C4stor on Wednesday December 02, 2020 @03:17AM (#25274270)
Academia is doing a lot of advances every year. The fact it didn't make _this one_ is not really relevant to postulate that academia is inefficient.

It happens that the team at deepmind is apparently pretty damn good at deep learning problems, so they're going faster than matching academia labs.

It's not to say that academia has none of the problems you mentioned, but it's imo unreasonable to expect that, in a world where both public and private labs exist, only public ones would make advances.

Re:AlphaFold: a solution to a 50-year-old grand challenge in... by krull10 on Wednesday December 02, 2020 @08:14AM (#25276024)
I would say that is most likely due to a massively higher salary and no teaching responsibilities. Academia can’t compete on salary with industry in AI / data science.