alt Hacker NewsWith this plus the weather model announcement. I’m curious what people think about the meta question on why corporate labs like Google DeepMind etc seem to make more progress on big problems than academia?
There are a lot of critiques about academia. In particular that it’s so grant obsessed you have to stay focused on your next grant all the time. This environment doesnt seem to reward solving big problems but paper production to prove the last grant did something. Yet ostensibly we fund fundamental public research precisely for fundamental changes. The reality seems to be the traditional funding model create incremental progress within existing paradigms.
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I can only speak for the weather models (since it is in my domain). The answer is that the issues are much more engineering and scaling/infra issues than theoretical issues, and google is good at engineering (or attracts people that are).
Where exactly do you think the idea for a quantum computer came from in the first place?
I did quantum computing research in university. We did meaningful work and published meaningful research.
Around 50% of our time was spent working in Overleaf making small improvements to old projects so that we could submit to some new journal or call-for-papers. We were always doing peer review or getting peer reviewed. We were working with a lot of 3rd-party tools (e.g. FPGAs, IBM Q, etc). And our team was constantly churning due to people getting their degrees and leaving, people getting too busy with coursework, and people deciding they just weren't interested anymore.
Compare that to the corporate labs: They have a fully proprietary ecosystem. The people who developed that ecosystem are often the ones doing research on/with it. They aren't taking time off of their ideas to handle peer-review processes. They aren't taking time off to handle unrelated coursework. Their researchers don't graduate and start looking for professor positions at other universities.
It's not surprising in the slightest that the corporate labs do better. They're more focused and better suited for long-term research.