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11/18/2005
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Q&A: Bill Gates On Supercomputing, Software In Science, And More

Bill Gates talks to InformationWeek about how work done at Microsoft Research can apply to science, medicine, and engineering; how more powerful desktop processors can improve user interfaces; and his evolving role at Microsoft.

The guys in the Cambridge [U.K.] lab have probably done the most of it. But again, it's about software, and the solutions that come out of these software things are valuable. If you can, for example, let somebody submit a job onto the Internet and find the cheapest place to run it, that's not just interesting for scientific cluster computing, that's interesting for business computing. Say I just happen to have a big analysis that I rarely do, or say that I'm in a disaster-recovery situation, where I'm trying to submit work out to be done remotely that would usually be done internally. These techniques of describing these resources, and letting things be visualized--we'll get plenty of benefits from these advances in the business realm. When we hired Heckerman and Horvitz, we were saying machine learning is this great thing for all the things we do.

InformationWeek: When we met back in September, we were talking about the shortage of computer science graduates in the United States, and that if that trend holds up, what it might mean for Microsoft years down the road. This trend of computing becoming integral to scientific advances, and even, as you pointed out, to the curriculum, is producing college students or graduate students who are in these scientific disciplines but are also quite skilled programmers. Has this outreach that you're doing to the high-performance computing community helped you attract a different class of candidate to Microsoft?

Gates: The issue about the shortage really is not going to be about Microsoft, because we have the most interesting jobs in software, and we can pay people super well. The shortage is more about the field as a whole. I mean, our customers need people who understand computer science. That's 90% of the thing. If anything, you could actually say the fact that we need software understanding to advance the sciences means the shortage is all the more acute, because you need people sitting in these computer science classes that then go off and really focus on life sciences, and focus on environmental sciences. As software is becoming this key thing, in the way that math was historically, you say, "Wow, how are we going to deal with all these people signing up for these computer science courses?" Well, quite the opposite, computer science departments have the problem that they can't keep their researchers. Part of the economic equation was that they were the teaching assistants for the computer science classes. And as those have gone down in size, that hurt.

So the world at large needs more scientific understanding. The fact that these understandings allow us to make advances in medicine, and understanding economics, and the environment should make the field all the more attractive. If you're a kid, a young, supersmart kid who says, "Hey, global warming, I want to contribute to that," boy, you'd better learn about data modeling and software, if you want to make a contribution there. You're going to take a bunch of software courses, as well as atmospheric science type courses. So it just shows we need to do a better job of painting the picture of the kind of opportunity and impact you can have, so that instead of such a high percentage of people going to, say, hedge funds or something, they'll come and help global warming, and a new AIDS vaccine, and things like that.

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