I just finished my PhD in CS at Georgia Tech, so I'll share my two cents on the topic. (My field was programming languages and compilers.) I wouldn't characte

I just finished my PhD in CS at Georgia Tech, so I'll share my two cents on the topic. (My field was programming languages and compilers.) I wouldn't characterize graphics as the "soundest" field. I might give that title to formal methods, where the bar for publication is often a machine-verifiable proof of correctness. Of course, graphics is math-heavy, too. A lot of the good graphics folks I know started off as mathematical physicists. For that matter, many sub-disciplines within CS are quite math-heavy. For my own dissertation, I developed static analyses of programs. To do so, I modeled the semantics of a programming language as a mathematical relation on machine states. I then defined new (finitely computable) relations---the analyses---and I proved these are sound simulations of the semantics relation. Plenty of math involved. Theory folks do plenty of math on the complexity and correctness of algorithms. Machine learning involves lots of probability and statistics. Even the top-notch human-computer interaction people know statistics well. I could go on. But, I think you could find a way to do some "real" math in any field within CS. (Though I've noticed each sub-discipline has its own self-aggrandizing definition of "real.") As far as how much of the article resonated with my own experience, I would have to say not much. I had plenty of cordial debates with professors, but ultimately, we would arrive at either a theorem or a contradiction, and then the debate was ended. No feelings hurt. No ego assuaged. Just a truth uncovered. The one part of the article that does ring true is the myopic vision of the world one receives in academia. Academia takes center stage as the noblest of all possible pursuits. The thrill of publication and peer recognition can be intoxicating, especially if you're the kind of person who is obsessed with publicly validating their own intelligence. I'm now taking a year off from academia to work full-time for my two startups, but a part of me feels like I'm selling out by not going on to become a professor right away. My own advisor warned strenuously me to continue publishing, lest the "jealous priesthood" of academia reject my attempt to return. I know enough, though, to know that he's right. If I don't continue to publish, academia will cut me off, regardless of how might money I might make doing startups. My parting advice to potential grad students in CS is: (1) choose a field that's growing rather than shrinking, and (2) find an advisor with whom you can develop a comfortable working relationship. After that, lots of hard work and a modicum of smarts can get you the rest of the way.