Читать книгу Ranger Games: A Story of Soldiers, Family and an Inexplicable Crime - Ben Blum, Ben Blum - Страница 14

Alex and I don’t much resemble family. As a kid I was skinny, angular, and odd, a classic math nerd. Alex was lantern-jawed, fit, and popular, a classic hockey jock. The more we talked about his story, though, the more we discovered unexpected affinities between us. It began to seem that at the far extremes of nerd and jock there was some kind of strange convergence. After a lifetime of pursuing our childhood dreams with single-minded focus, he and I had both ended up as naive tools of forces far beyond our ken, two very different kinds of muscle.

Growing up, I had always been so daunted by the complexity I saw laid out in the face whose voice I was listening to—twitching nostrils, forced smile, tongue folding back over withheld laughter, secrets and simplifications and lies—that eye contact felt like two live wires touching. Math was safer. Massive shapes interlocked in the darkness with comforting impersonality. Evangelicals like to offer up the intricacy of the eyeball as evidence of intelligent design. For me, mathematical order so far surpassed the haphazard mess of the body that biological typologies struck me as arbitrary, ugly, absurd. Math was simply true. Like antennae poking out of a fogbank, surface facts always suggested deeper purposes, buried cities. Diving for their hidden interconnections was as much a form of prayer as anything I’ve heard my religious friends describe. But unlike religious faith, mathematical faith was rewarded with concrete affirmation: after plunging for hours through the gloom, going so deep your breath ran out over and over, forcing you to retreat back to the light gasping and confused, you would suddenly see it—perfect, glorious, gigantically indifferent to the mind that had stumbled on it. Paul Erdös, the itinerant, speed-addicted Hungarian who pioneered modern combinatorics, said of particularly pretty proofs, “That’s one from the book.” He meant the book of God.

Adults reacted to my talent as if I had a fabulous occult power. Soon I too was seduced. I’d peer down from the Mile High Stadium bleachers at 70,000 Broncos fans dropping off in murmuring tiers, or squeeze into the mall escalator’s infinite extrusion of perfumed blouses and curls, or cut between skiers under pine trees fat with oblong pads of snow, and out of nowhere glory would fill my whole throat: a web of field lines and force vectors shimmered out through everything, and no one could see it but me. “Statistically speaking,” I would think, “I am probably the smartest person here.”

Whenever Alex told me about his preparations in high school for basic training, I recognized the loneliness and glory of my own childhood self-absorption. Like me, he perplexed those closest to him. Like me, he sustained himself with fantasies of a world that would celebrate his idiosyncrasies—in his case, Ranger Battalion, where he was sure he would finally encounter true believers like himself who stood ready to give up their lives for the people and the country they loved. The culture he encountered there may have frightened him at first with its frank, relentless focus on killing, but it also gratified and expanded his sense of myth. He is lucky never to have faced the reality of war, which I imagine does for military idealism approximately what grad school does for the pure love of knowledge as an end in itself.

The most important mathematical results of the twentieth century concerned the limits of mathematical knowledge. Gödel’s incompleteness theorem showed that not all true theorems could be proved; the Church-Turing thesis led to the understanding that not all problems could be solved algorithmically. The rest of the world shrugged—of course there were some things you couldn’t do with math. One look at the spacey, stuttering basket cases who were good at it suggested that interpersonal communication, fashion, and hygiene were among them. But for mathematicians and scientists of all stripes, the blow to their faith in the descriptive power of their language was shocking. The relation of scientists and nonscientists to the inexplicable is very different. What Keats called negative capability, “when a man is capable of being in uncertainties, mysteries, doubts, without any irritable reaching after fact and reason,” is a daily necessity for social beings. We won’t ever understand why people make the crazy choices they make, love the awful music they love, believe in astrology or baseball or God, but having good manners entails accepting these mysteries. Art entails producing them. Scientists are often bad at both. After leaving the University of Colorado for an abortive two-and-a-half-year effort at a normal high school experience, I started at Stanford as a shy seventeen-year-old with a suitcase full of Nine Inch Nails T-shirts and combat boots and a schedule full of graduate seminars, utterly baffled by actual human beings, utterly confident in my ability to model them algorithmically.

I wasn’t the first to overestimate myself in this way. After the wild enthusiasm of the field’s early years in the 1950s—the efforts at representation of the world’s entire store of knowledge in logical form, the gradual comprehension that logical propositions were too rigid and inflexible to have much predictive use, the blind alley of “fuzzy logic,” the probabilistic models of belief that grew to dominate the field—artificial intelligence researchers came to understand that the big problems of memory, reasoning, language, and consciousness were much more complex than they had imagined. By the time I went knocking on those researchers’ doors, breaking naive undergraduates of their hazy dreams of programming themselves a computer friend had become a distasteful but necessary part of the job. The fundable problems were the kinds you could get traction on: recognition of handwritten zip codes on envelopes, the parsing of Internet search queries, automated flight control of helicopters. The first major project I was invited to participate in sought to compute Nash equilibria in structured strategic scenarios. Funding came from the Department of Defense.

It was an exciting time to be in Silicon Valley. Google’s first server, scaffolded on rainbow-colored Legos, rested in a display case in the Gates Building basement. Movies and magazines were awash in romanticized hacker imagery. We few undergrads who had bulled our way into research were a club every bit as proud, in our way, as the Rangers. When we put together presentation slides for the yearly funding meeting with a stodgy, uncomprehending naval officer and a few of his staff, we all laughed together at how shamelessly we were using clip-art icons of tanks and soldiers instead of the usual abstract blue circles as nodes in our directed acyclic graphs. The joke was on the military: we were a bunch of apolitical nerds funneling away their bomb money to do awesome mathematics, all of which was far too theoretical—practically aesthetic in its aims—to have any chance of military application.

Eight months into the war in Afghanistan, when the legendary Defense Advanced Research Projects Agency (DARPA) announced a $1 million prize for the winning robotic vehicle in an unmanned race across the California desert, I watched hundreds of casually pacifist nerds like me in computer science departments around the country leap into an excited spasm of whiteboard sketching, number crunching, and microcontroller programming. I wasn’t surprised. I wasn’t even bothered, aside from feeling a jealous pang or two at how much cooler their projects were than my own. If you have ever done technical research, you know just how right