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Web-only Exclusives
November 30, 2000

From Our Correspondent: Hirohito and the War
A conversation with biographer Herbert Bix

From Our Correspondent: A Rough Road Ahead
Bad news for the Philippines - and some others

From Our Correspondent: Making Enemies
Indonesia needs friends. So why is it picking fights?

Asiaweek Time Asia Now Asiaweek story

Playing by the Numbers

Can Deep Blue acquire human smarts?

By Jim Erickson and Luis H. Francia / New York


MAY 4, 1997, MAY be remembered as an occasion when science fact began to resemble science fiction. In New York, in a room packed with reporters and TV cameras, an IBM computer named Deep Blue took on world chess champion Garry Kasparov and dispatched him in 45 moves. The significance was not that circuitry had triumphed over synapses. In their first man-versus-machine contest last year, Deep Blue beat Kasparov in the first game and forced two draws before going down 2-4. This time, what mattered was the way the re-programmed computer won, displaying an artificial intelligence that to some was eerily akin to human intuition. "Deep Blue made many moves that were based on understanding chess, on 'feeling' the position," says Susan Polgar, the women's world champion. "We all thought computers couldn't do that."

IBM computer scientist Hsu Feng-hsiung did not shout a Frankensteinian "It's alive!" when Kasparov retired in the second game after handily winning the first. But the 39-year-old Taiwan native, whose doctoral work at Carnegie Mellon University established the bloodline for IBM's marvel, must have felt a surge of satisfaction. After years of frustration, researchers are close to making computers that can -- in their inelegant electronic way -- think, and think effectively. "We are now getting to the stage where we are solving problems [like a chess match] that used to require human intelligence," says Tan Chung-jen, China-born manager of the Deep Blue project.

Computers have long been superb at number-crunching. But their logic circuits are no match for the mind when drawing upon complex data -- experience, knowledge, perception, probability -- to reach a conclusion or plan a strategy. The IBM machine, which is equipped with 32 ultra-fast microprocessors, can't even learn from its own mistakes except in a rudimentary way. "Deep Blue is like a kid with enormous talent," says Hsu. "But it still doesn't know chess."

For more than two decades, scientists have tried to overcome the limitations of the microchip by imitating in software what little is known about human thought processes. One programming technique, called an "expert system," tries to give computers the ability to sift correct answers from memory banks stuffed with human knowledge. Another, called "neural networking," is a form of automated learning based on laws of probability. None has worked well on chess-playing computers, says Eric Winkler, chief executive of Saitek, the world's largest maker of electronic chess machines.

What does work: brute computational force. Deep Blue's processors acting in concert can analyze 200 million chess moves a second. That means the machine can mechanically examine possible moves and counter-moves 12 to 14 plays ahead in the allotted three minutes. Still, processing power alone is not enough to ensure victory. The number of permutations in any game has been estimated at 10 to the 40th power. That is roughly the number of atoms in the universe, according to Winkler, far beyond Deep Blue's calculus. So IBM hired American grandmaster Joel Benjamin. He helped programmers sort the few strong moves from billions of weak ones and imbue the machine with a crude judgment to steer it toward a winning strategy. "The science is to get rid of the garbage early in the process so [the computer] can focus on quality," says Winkler.

But is the machine capable of acting on gut instinct? No, says Hsu, though its remarkable speed "can make it appear to have intuition." The computer lacks Kasparov's experience, "so he can make better judgments." Deep Blue is unable to look across the board, size up its opponent's weaknesses and deviously exploit them. In the series last year, Kasparov used the machine's predilections against it. IBM programmers this year tried to level the field by feeding the computer data from dozens of games Kasparov has played. The Russian responded by changing his style.

The outcome of the match, unknown at midweek, ultimately won't matter as much as what scientists learn in the process. Tan says Deep Blue's logic equations can be applied to more practical fields -- molecular dynamics, pharmaceutical research, data-analysis and air-traffic control, for example. Super-smart computers may become widely available before long. IBM has built a portable version of Deep Blue, called Deep Blue Jr., capable of evaluating 10 million chess positions and playing at grandmaster level. But the amiable R2D2s and malevolent HALs of science fiction movies will likely remain fantasy, Winkler says, because humans "are unable to introspect perfectly our own thought processes." You can't teach what you don't know.


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