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Matt Welsh of Google—formerly of Harvard, Berkeley and Cornell—is a deservedly well-read blogger in the computing community.  He’s also somebody I’ve admired since his early days in grad school as a smart, authentic person.

Matt’s been working through his transition from Harvard Professor to Googler in public over the last year or so, and it’s been interesting to watch what he says, and the discussion it provokes.  His latest post was a little more acid than usual though, with respect to the value of academic computer science.  My response got pretty long, and in the end I figured it’d be better to toss it up in my own space.

Matt:

Rather than run down work you don’t like—including maybe your own prior work, as assessed on one of your dark days—think about the academic work over the last 50 years that you admire the hell out of. I know you could name a few heroes. I bet a bunch of your blog’s readers could get together and name a whole lot more. Now imagine the university system hadn’t been around and reasonably well-funded at the time, because it was considered “inefficient when it comes to producing real products that shape the world”.   It’s sad to consider.

Here’s another thing you and your readers should consider: Forget efficiency. At least, forget it on the timescale you measure in your current job. Instead, aspire to do work that is as groundbreaking and important as the best work in the history of the field. And at the same time, inspire generations of brilliant students to do work that is even better—better than your very best. That’s what great universities are for, Matt. Remember? Sure you do. And yes—it’s goddamn audacious. As well it should be.

Now, can you get up and be actively audacious every day? Nobody can, not even the Greats. So we take a portfolio approach at all levels: lots of universities, lots of research grants, lots of individual faculty and students, and—for some individuals—lots of different career phases to see where your changing interests and skills fit best. It’s good to move around. But all the while, you have to respect the portfolio, Matt. It’s been working fabulously over the long term. And it’s done so on a tiny fraction of the budget of corporate America, a tiny fraction of the tax base.

The funny thing about your timing here is that the short-term view is actually really rosy right now—times are great for academic/industrial fluidity in computing. Companies and VCs and pundits are flocking to academic leaders for ideas and guidance. Academics are more aware than ever about what’s going on in industry, and some of the really good ones have taken the plunge into companies to do the tech transfer. Times are really good, even on the small timescale.

Can things get better? Sure they can. Is the university research model perfect? Of course not. We should have a portfolio of experiments there too, including new models for tech transfer and collaboration between academia, industry, and venture funding. (I blogged about one of my experiments recently). So by all means go back to your post and distill down some of the constructive parts.  Spend time on some of them.  You’re not alone in wanting to experiment with these models and improve the pipeline, and there’s a good constructive conversation to have.

Meanwhile, stay positive! Life is good. Research is good! You have a big platform there (and I don’t mean all those computers you can log into). Use it for good. Remember your heroes. Emulate and inspire.

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6 Comments

  1. Great post, Joe, and I agree that it makes sense to take the long view when it comes to academic research. To be clear, I never said that doing startups was the only (or even the best) way to have impact on the world as an academic. But there seem to be a lot of academics who would like to have that kind of impact, if they could only afford to take the risk, and had the resources and business connections to do so. So you might argue my post was addressing a niche market for a certain kind of academic, so to speak. It was not intended as a polemic against academia in general, although for some reason any time I post on my blog it’s interpreted that way :-)

  2. Love the optimism, Joe. But your response doesn’t address the core question, which I take as “What is the role of academic computer scientists, and the academy in general, in system building & churning out working code?” Back in the day, great systems groups not only wrote great papers; they also built great systems. Today, exemplary projects like MadLib or D3.js are exceptions rather then the rule. Why are so many of today’s great systems (proprietary or open source) being designed and built outside of universities? Is it that academics dont have the resources to compete with industry? Has the growth in size and prestige of CS departments led faculty to seek more “fundamental” discoveries? Is the low-hanging system-building fruit all gone? Or, has the allure of big bucks lead researchers to quickly take viable systems outside of the university, making them easier to commercialize? Are we losing something as a discipline by not having more researchers and students disseminating their results as working open source code? Just a few questions this exchange raised for me.

    • Tap — I don’t know if those were Matt’s core questions, but they’re good questions. Here’s what I wrote on this front in the MADlib paper that’s appearing at VLDB this fall (I realize it’s not in the blog post I linked to):

      In previous decades, many important open source packages originated in universities and evolved into significant commercial products. Examples include the Ingres and Postgres database systems, the BSD UNIX and Mach operating systems, the X Window user interfaces and the Kerberos authentication suite. These projects were characterized by aggressive application of new research ideas, captured in workable but fairly raw public releases that matured slowly with the help of communities outside the university. While all of the above examples were incorporated into commercial products, many of those efforts emerged years or decades after the initial open source releases, and often with significant changes.
      Today, we expect successful open source projects to be quite mature, often comparable to commercial products. To achieve this level of maturity, most successful open source projects have one or more major corporate backers who pay some number of committers and provide professional support for Quality Assurance (QA). This kind of investment is typically made in familiar software packages, not academic research projects. Many of the most popular examples—Hadoop, Linux, OpenOffice—began as efforts to produce open source alternatives to well-identified, pre-existing commercial efforts.

      MADlib is making an explicit effort to explore a new model for industry support of academic research via open source. Many academic research projects are generously supported by financial grants and gifts from companies. In MADlib, the corporate donation has largely consisted of a commitment to allocate significant professional software engineering time to bootstrap an open source sandbox for academic research and tech transfer to practice. This leverages a strength of industry that is not easily replicated by government and other non-profit funding sources. Companies can recruit high-quality, experienced software engineers with the attraction of well-compensated, long-term career paths. Equally important, software shops can offer an entire software engineering pipeline that cannot be replicated on campus: this includes QA processes and QA engineering staff. The hope is that the corporate staffing of research projects like MADlib can enable more impactful academic open source research, and speed technology transfer to industry.

      So MADlib is one experimental model for getting industry and academia aligned in a way that leverages their mutual strengths. I’m sure there are others.

  3. Thanks for posting this, Joe. I think you’re spot-on.

    But I’ll point out one additional word I haven’t seen much in either post: Education. Those millions of dollars also went towards educating future researchers, some of whom will make future breakthroughs, found future startups, rewrite Google’s indexing system, and so on. The cost of a graduate student through 5 years of a Ph.D. program is, plus or minus, $350,000. Now, it’s nice when that money produces {good breakthroughs + a highly trained researcher}, but there’s significant value alone to the human product that comes out in the end as well.

    • Excellent point. And the industry is tangibly happy that we provide that service — students with PhDs in Computer Science are in *very* high demand and companies pay them accordingly.

  4. Just to be clear, im a nobody. Just found the discussion interesting. I will simply point out a perhaps ‘ancient’ social system that supports both the points of view. This system suggests that there are 4 social goals of humans and each with its own “currency”/value – (1) seeking knowledge/experience of the real or platonic world (2) seeking power (my way is the right way) (3) seeking wealth, material things, money etc (4) offering services to people. HIstorically it appears that each step leads to higher pleasure (and leads to less regret and thus more “rational” in the long term). Research will explore territory barely anyone had the courage to think about before. Entrepreneurs can cash in on it and do “real world stuff” (as they define real). In other words, both these points of view are completely valid, and all they do is reveal the psychology of the bloggers, than a somewhat objective description of “reality”. btw, im from india and this so-called-social-system is the “caste” system fwiw. Almost every activity has a social impact — it is what one likes doing/derives pleasure out of.


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