All of those quotes are conditioned on the premise that you're doing research which purports to be relevant to industry. In that context I agree with Matt.
> Now, I don't think all academic research has to be relevant to industry. In some sense, the best research (albeit the riskiest and often hardest to fund) is stuff going way beyond where industry is focused today. Many academics kind of kid themselves about how forward-thinking their work is, though. Working on biomolecular computation? That's far out. Working on building a faster version of MapReduce? Not so much. I'd argue most academics work on the latter kind of problem -- and that's fine! -- but don't pretend you're immune from industry relevance just because you're in a university.
This paragraph makes this point abundantly clear: there's plenty of research that is focussed on expanding the field and is discovering problems that will exist once industry catches up. Fantastic. It's risky to try and find the future, but someone has to do it, and I think (based on this and his other writing that I've encountered) Matt would agree that time spent in industry is of dubious utility to those folks[0].
For research that is attempting to tackle extant problems encountered by industry, though, the researcher would be well served by ensuring that the problem they're attempting to solve is actually extant and that the assumptions they're making in trying to solve it don't simply sound reasonable but actually reasonably embody assumptions underlying real (aka industry) deployments. Otherwise they may get a lovely paper which solves a problem that nobody actually has or presents a solution that is impractical because it assumes things which are, in real deployments, incorrect.
[0]: On one hand, it might give them a better feel for in which direction a tractable future lies, but by the same token it might prevent them from exploring potentially fruitful avenues by constraining their thinking.
> Now, I don't think all academic research has to be relevant to industry. In some sense, the best research (albeit the riskiest and often hardest to fund) is stuff going way beyond where industry is focused today. Many academics kind of kid themselves about how forward-thinking their work is, though. Working on biomolecular computation? That's far out. Working on building a faster version of MapReduce? Not so much. I'd argue most academics work on the latter kind of problem -- and that's fine! -- but don't pretend you're immune from industry relevance just because you're in a university.
This paragraph makes this point abundantly clear: there's plenty of research that is focussed on expanding the field and is discovering problems that will exist once industry catches up. Fantastic. It's risky to try and find the future, but someone has to do it, and I think (based on this and his other writing that I've encountered) Matt would agree that time spent in industry is of dubious utility to those folks[0].
For research that is attempting to tackle extant problems encountered by industry, though, the researcher would be well served by ensuring that the problem they're attempting to solve is actually extant and that the assumptions they're making in trying to solve it don't simply sound reasonable but actually reasonably embody assumptions underlying real (aka industry) deployments. Otherwise they may get a lovely paper which solves a problem that nobody actually has or presents a solution that is impractical because it assumes things which are, in real deployments, incorrect.
[0]: On one hand, it might give them a better feel for in which direction a tractable future lies, but by the same token it might prevent them from exploring potentially fruitful avenues by constraining their thinking.