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TR: What is a symbolic science?

NM: Something with deep abstractions described by lots of data. Vast amounts of data-and analyzing abstract data is one of the most important frontiers in biology and medicine. So understanding which of your genes have this, that and the other thing, or which things are being expressed in your body right now. What proteins are in over- or undersupply. Where is there a feedback control system that’s screwed up. We’re on the verge of figuring out that or a million other very complicated systems. A key tool in that’s computing. So bioinformatics, bioinformatics algorithms. Most of that stuff is at its complete infancy. One thing that’s amusing to me is that when I visited proteomics companies, you get people, although they use computers, they use them in completely boneheaded ways. So everybody has big SQL databases, big Oracle databases, under the faith that that’s a good thing to do, when it’s completely ill suited. The relational database was designed for tasks such as tracking stock room inventory or managing employee information; it was not designed for manipulating genomic base pairs and genetic information. So somebody needs to invent a bunch of stuff there. But more than that, biology and medicine are about reverse-engineering a very complicated machine. The detailed understanding of all the mechanisms and pathways by which things are regulated and controlled, the ways in which disease disrupts those regulations and how we can put them right, that’s all incredibly complicated. Well, that suggests all kinds of opportunity. What tools are missing? What are the analysis techniques that you need to do? There are a million things.

TR: We have all this growth in technology, but you have been quite vocal in also pressing for more basic science.

NM: Basic science is the fundamental well from which all this stuff is watered. Ironically, basic science is being given increasingly short shrift. DARPA [the U.S. Defense Advanced Research Projects Agency] funding for computer science is probably the single most successful government program in the history of governments-it led to this entire revolution in computing. Yet most Silicon Valley companies that are the beneficiary of that don’t invest in fundamental research. Then you get the ludicrous thing of people in Congress saying they want more relevant research. No, you should have less relevant research.

I’ve done extensive modeling of all of this. If you’re a company that lives hand to mouth, don’t do research, okay. You don’t need me to tell you that. If you’re a company that has steady cash flows, then you should work at whatever level you can afford. So if you’re a company that intends to be around 20 years from now, like a Microsoft, you are losing money if you don’t do research. It is an incredibly profitable investment only open to a limited club-the people who can afford to take a long-term view. And that’s an industrial research context. At the government level, you really should swing for the fences.

You could make a case that research funding really won the Cold War, because it was those economic things that stoked the economy. As soon as the Soviets went from being our enemies to being potentially our friends, [people said,] now let’s stop giving lots of money to science. Well, that doesn’t make any sense. Fundamental science has been the best investment the government’s ever made.

TR: A big mark against basic research in industry is that the firms who support it don’t always capture the benefit of it-Bell Labs with the transistor, Xerox with so much of modern computing.

NM: Whether you’re expanding overseas or you’re doing any business decision, you can find someone who screwed it up and caused lots of hurt to their company. It hasn’t stopped people from doing it.

So take Xerox as an example. The same era that they started PARC [the Palo Alto Research Center, birthplace of the graphical user interface, Ethernet and other elements of digital computing], they bought a company called Scientific Data Systems. They lost a billion dollars in 1970 dollars on that. More money than they’ve spent on PARC the entire time they’ve had PARC. Nobody gives them any shit for that anymore. Everyone says, oh, Xerox screwed up PARC. They didn’t screw up PARC. PARC invented the laser printer. That one invention alone paid for PARC many times over. Yet people give Xerox a black eye for this. Why? Because they think, “But they should have done more.” Well, if you do shoulda, woulda, coulda, you’re going to drive yourself crazy. The problem that Xerox had-the fundamental problem-is that Xerox didn’t understand computers. That’s why they lost the billion dollars in that other merger. That’s also why they couldn’t commercialize any of the other computer inventions.

So you add it up, investing in basic research makes huge sense for companies. But it makes even more sense for the government. By the way, I’d love to have the rest of the world join us, because research is the kind of thing that feeds on other research. The fundamental researcher in China that isn’t being funded today might be the one who if he was funded would find the cure to the disease I’ll get in 20 years.

TR: You mentioned Microsoft as one company doing fundamental research, which you had a role in. What about the rap that Microsoft is not able to innovate?

NM: When I first got into computers, there was no Microsoft. IBM was considered this big company that dominated the industry and wasn’t very innovative, yet if you look at their patents or the history of the first things that they did, IBM was the most innovative company in large computers. IBM got a reputation for not being such because the computers they sold generally made sense, and their innovation was packaged in something that was incredibly pragmatic and practical.

Fast-forward 30 years, Microsoft’s in the same position. Microsoft tends to package its innovation in things which are incredibly practical. Yet they often are very, very innovative. Sometimes in incremental ways, sometimes in revolutionary ways. Let me take my favorite example of a Microsoft program that was way ahead of its time. Windows. I was development manager when it was 2.0. Everybody now acts like Windows was part of the firmament, destined to be a success. No, it was an incredibly hard battle to convince the industry that the graphical user interface was good. The key ideas were invented at Xerox; Apple and Microsoft both commercialized it. And both Apple and Microsoft deserve a tremendous amount of credit for that.

TR: Let’s come back to something you mentioned right off the bat-a theory that accounts for this new period of exponential growth. Can you elaborate?

NM: People want to have the next Silicon Valley. The interesting thing is not so much the next Silicon Valley in a geographic sense, it’s what are the next [technological] areas that will undergo this kind of growth two, five, 10 years and 50 years from now? And how does that reshape the world? I think it’s possible to go about that in a more deliberate way. To actually say, this is what you should look for. This is how you should do it-and then nurturing them over that hump.

But I’m still working on it.

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