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Academic research that unknowingly (or sometimes even knowingly) duplicates secret industry work is much more valuable than this discussion indicates. Sure, it'
by samth 11y ago
Academic research that unknowingly (or sometimes even knowingly) duplicates secret industry work is much more valuable than this discussion indicates. Sure, it's not valuable _to Google_ for someone to publish things they already know. But everyone else benefits. If people at Google want their research to stop being duplicated, they should publish it.
Of course, if your goal is that Google adopt your new system in their data centers, then you need to know what they already do. But the problem with that model of research is the initial goal, not the way it's currently executed.
- mdwelsh 11y agoI'm not so worried about duplication by academics -- that does not happen often -- but rather about academic research that's just wrong: makes bad assumptions, uses a flawed methodology, fails to address the general case.
- kenjackson 11y agoIf industry could provide better platforms (up to date, not hand me downs or neutered versions of their real product) then I think you might see better forms of this research. For example, I'd love to improve search relevance, but w/o having access to Google's search engine to build on, it's pretty hard. That's my suggestion. :-)
- mdwelsh 11y agoWhile I agree in general that opening up opportunities for academic-industry collaboration is good, I don't think it's practical for academics to work on problems at true industry scale. Academics don't have access to the resources, personnel, or funding required to do that kind of work. An academic lab can do many things of relevance to industry -- but not everything. Google recently open sourced its TensorFlow plstform specifically to enable researchers (and others) to build upon and improve it -- trying to avoid the problem with MapReduce (where a bunch of clones came out that were, at least initially, inferior to the original).
- dadkins 11y agoIt would be really nice if they would go ahead and release the Google version of MapReduce now that they've learned their lesson. It's not too late for everyone to learn from the original, and it's no longer a competitive advantage now that anyone can run a Hadoop job on AWS on demand.
- js8 11y agoI think I agree with samth - it's not the academia, but the industry who needs to open up. Especially Google has a reputation of being very secretive.
- pklausler 11y agoGoogle patents a lot of cool stuff, actually. But the ideas tend to not get noticed in academia; when was the last time you saw a patent in a bibliography?
- nickpsecurity 11y agoAcademia patents tons of stuff. They just put that in patent applications and technology portfolios instead of bibliographies.
- jldugger 11y agoThe point is that patents don't appear to contribute to the sum total knowledge that academics build on top of. They're by and large intellectual dead ends, if profitable ones.
- nickpsecurity 11y agoOh I mostly agree. Some organizations will only fund you if they get IP out of it. Many significant tech in that area. But it's mostly an after the fact make money thing. Or just bullshit altogether.
- mdwelsh 11y agoSee my reply above - I'm all for industry opening up where possible, and a lot of stuff gets open sourced these days (hell, didn't Facebook even open source its data center designs?). Opening up technology doesn't necessarily mean academics will focus on the right problems, though.
- nickpsecurity 11y agoYou and samth seem to be missing the point: academic research is often built using methods that will ensure no real-world success while aiming to achieve real-world success. Factoring in real-world constraints, best practices, and existing work-arounds will let academics achieve better results on average. Baseline of practicality goes up. And again, these are all academic projects that aim at being practical. The point is supported by a number of academics that incorporate real-world information and constraints into their work to produce deliverables that advance state-of-the-art and are useful. Examples that come to mind are: Haskell/Ocaml/Racket languages, CompCert C compiler, Microsoft's SLAM for drivers, SWIFT auto-partitioning for web apps, Sector/Sphere filesystem, the old SASD storage project (principles became EMC), old Beowulf clusters, ABC HW synthesis, RISC-V work, and so on. So many examples of academics keeping their head in the real-world instead of the clouds to making a name for themselves with awesome stuff with immediate and long-lasting benefits. I'm not Matt but I'm guessing he'd rather see more examples like this than, say, a TCP/IP improvement that breaks compatibility with all existing Tier 1-3 stacks and whose goal is to improve overall Web experience. Yes, there are people working on those. ;)
- samth 11y agoOf course, there's tons of academic research that does all of those things. And I of course agree that too much academic software is "works on my grad students machine"--an enormous amount of my time on Racket is spent on real-world works-in-practice issues. But this doesn't seem like it's a particular issue of industry-relevant systems work, just Sturgeon's Law. Also, failure to address the general case is not so bad--it just means that the next part of the general case has to be addressed by the next researcher. Finally, I think the real issue is academics who have an idea, and cloak it in pseudo-relevance to industry to sell it. A program analysis framework isn't suddenly industry-relevant now that it applied to JavaScript, and we should just be ok with not chasing the latest industry fad.