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> The people who implemented these systems have all received their phds from academic CS institutions and they used bits and pieces of existing distributed syst

> The people who implemented these systems have all received their phds from academic CS institutions and they used bits and pieces of existing distributed systems research, but they did their innovative work in the context of commercial companies, not academic CS departments. Three thoughts. First, the title of the talk is "Systems Software Research is Irrelevant", not "Systems Building in Academic Departments is Irrelevant". e.g. the talk discusses plan 9. The distinction the talk makes, I think, is between commercial products and R&D not between industry and academia. In that sense, I think the stuff out of google (mapreduce up through tensorflow) are good examples of that trend reversing Second, industry R&D has almost always lead the charge on developing large systems in CS. That's not new. Third, as you noted, "[many of] the people who implemented [and more important lead the design of] these systems have all received their phds from academic CS institutions and they used bits and pieces of existing distributed systems research". One role of CS academic research is to build foundational ideas and then crank out competent researchers who are able to build real systems/algorithms/companies on top of those ideas. Just because TensorFlow was developed at Google rather than UW doesn't mean that academic research is now irrelevant. > And what are they? There's a lot of OCaml, Haskell, and Scala code in the world. C# and the entire .NET family is a veritable treasure trove of academic pl ideas making it into production languages.

dunkelheit 8y ago
Good comments. They got me thinking, what exactly is "research" - I don't know what distinction Rob makes, but for me research software is software that is written with the main goal of publishing a paper in mind. In this sense mapreduce is emphatically not research software - it was first deployed into production and only then there was a paper (with production deployment serving as validation). A good counterexample would be not mapreduce but Stonebraker's c-store which then got commercialized as Vertica. > One role of CS academic research is to build foundational ideas and then crank out competent researchers who are able to build real systems/algorithms/companies on top of those ideas. Educational role is very important, but do phd graduates build on top of their research? Instead it seems, they learn the foundations (which were "research" a few decades ago), do a phd project on some very specialized and inconsequential thing and then go off to do real stuff at commercial companies.
- pasabagi 8y ago
  To use an example from another field - nothing would have seemed more specialized and inconsequential than clustered regularly interspaced palindromic repeats in bacterial DNA. But then, that turned into CRISPR. Working on obscure, niche stuff is how you actually contribute to science.
  - dunkelheit 8y ago
    Obviously I don't know much about biology, but are regular genome patterns with unclear functions such a common occurrence that they are seen as inconsequential? > Working on obscure, niche stuff is how you actually contribute to science. That's what they tell you (my favorite example BTW is conic sections - obscure and niche for millenia before it became known that they describe the orbits of planets). But is the deluge of highly specialized obscure papers really the consequence of free play of scientists' minds pursuing their own interests? Or is it more a consequence of the sheer number of phd candidates and postdocs that each need to achieve sufficiently novel results on a reasonable time scale with a fairly certain chance of success (objectives that are obviously in conflict)? Of course ground-breaking research can grow out of niche results. But for growth to happen someone should build upon and improve upon these results. It is difficult to build upon a research prototype that works barely enough to register a minimal improvement to some metric and is thrown out afterwards.
    - pasabagi 8y ago
      >someone should build upon and improve upon these results. I'm also not from a biology background - but I remember from doing philosophy, it was much more useful to find a paper that made some trivial advance in a very specialized area that you were interested in, than ten 'general' papers. I mean, if you're building something, and somebody has written a paper that addresses a part of your domain, it's gold dust - even if it's generally too niche for anybody to bother reading, even if it's substandard work. You're right that there are some kind of perverse incentives in the hothouse-production of phd theses, but I think in general, people should embrace the triviality and irrelevance of scientific work. Alchemy set out to answer the big questions of eternal life, and gold from lead, and ended up answering nothing. Science set out to answer questions like, how are colours in flower petals passed through generations? If you look at the history of 'big questions', it's way less illustrious than that of small, boring ones.

dunkelheit 8y ago

Good comments. They got me thinking, what exactly is "research" - I don't know what distinction Rob makes, but for me research software is software that is written with the main goal of publishing a paper in mind. In this sense mapreduce is emphatically not research software - it was first deployed into production and only then there was a paper (with production deployment serving as validation). A good counterexample would be not mapreduce but Stonebraker's c-store which then got commercialized as Vertica. > One role of CS academic research is to build foundational ideas and then crank out competent researchers who are able to build real systems/algorithms/companies on top of those ideas. Educational role is very important, but do phd graduates build on top of their research? Instead it seems, they learn the foundations (which were "research" a few decades ago), do a phd project on some very specialized and inconsequential thing and then go off to do real stuff at commercial companies.

pasabagi 8y ago
To use an example from another field - nothing would have seemed more specialized and inconsequential than clustered regularly interspaced palindromic repeats in bacterial DNA. But then, that turned into CRISPR. Working on obscure, niche stuff is how you actually contribute to science.
- dunkelheit 8y ago
  Obviously I don't know much about biology, but are regular genome patterns with unclear functions such a common occurrence that they are seen as inconsequential? > Working on obscure, niche stuff is how you actually contribute to science. That's what they tell you (my favorite example BTW is conic sections - obscure and niche for millenia before it became known that they describe the orbits of planets). But is the deluge of highly specialized obscure papers really the consequence of free play of scientists' minds pursuing their own interests? Or is it more a consequence of the sheer number of phd candidates and postdocs that each need to achieve sufficiently novel results on a reasonable time scale with a fairly certain chance of success (objectives that are obviously in conflict)? Of course ground-breaking research can grow out of niche results. But for growth to happen someone should build upon and improve upon these results. It is difficult to build upon a research prototype that works barely enough to register a minimal improvement to some metric and is thrown out afterwards.
  - pasabagi 8y ago
    >someone should build upon and improve upon these results. I'm also not from a biology background - but I remember from doing philosophy, it was much more useful to find a paper that made some trivial advance in a very specialized area that you were interested in, than ten 'general' papers. I mean, if you're building something, and somebody has written a paper that addresses a part of your domain, it's gold dust - even if it's generally too niche for anybody to bother reading, even if it's substandard work. You're right that there are some kind of perverse incentives in the hothouse-production of phd theses, but I think in general, people should embrace the triviality and irrelevance of scientific work. Alchemy set out to answer the big questions of eternal life, and gold from lead, and ended up answering nothing. Science set out to answer questions like, how are colours in flower petals passed through generations? If you look at the history of 'big questions', it's way less illustrious than that of small, boring ones.