http://www.nybooks.com/articles/23592
ilginc birkac yeri koteleyeyim..
QUOTE
In 1985, in Hamburg, I played against thirty-two different chess computers at the same time in what is known as a simultaneous exhibition. I walked from one machine to the next, making my moves over a period of more than five hours. The four leading chess computer manufacturers had sent their top models, including eight named after me from the electronics firm Saitek.
It illustrates the state of computer chess at the time that it didn't come as much of a surprise when I achieved a perfect 32–0 score, winning every game, although there was an uncomfortable moment. At one point I realized that I was drifting into trouble in a game against one of the "Kasparov" brand models. If this machine scored a win or even a draw, people would be quick to say that I had thrown the game to get PR for the company, so I had to intensify my efforts. Eventually I found a way to trick the machine with a sacrifice it should have refused. From the human perspective, or at least from my perspective, those were the good old days of man vs. machine chess.
Eleven years later I narrowly defeated the supercomputer Deep Blue in a match. Then, in 1997, IBM redoubled its efforts—and doubled Deep Blue's processing power—and I lost the rematch in an event that made headlines around the world. The result was met with astonishment and grief by those who took it as a symbol of mankind's submission before the almighty computer. ("The Brain's Last Stand" read the Newsweek headline.) Others shrugged their shoulders, surprised that humans could still compete at all against the enormous calculating power that, by 1997, sat on just about every desk in the first world.
It was the specialists—the chess players and the programmers and the artificial intelligence enthusiasts—who had a more nuanced appreciation of the result. Grandmasters had already begun to see the implications of the existence of machines that could play—if only, at this point, in a select few types of board configurations—with godlike perfection. The computer chess people were delighted with the conquest of one of the earliest and holiest grails of computer science, in many cases matching the mainstream media's hyperbole. The 2003 book Deep Blue by Monty Newborn was blurbed as follows: "a rare, pivotal watershed beyond all other triumphs: Orville Wright's first flight, NASA's landing on the moon...."
The AI crowd, too, was pleased with the result and the attention, but dismayed by the fact that Deep Blue was hardly what their predecessors had imagined decades earlier when they dreamed of creating a machine to defeat the world chess champion. Instead of a computer that thought and played chess like a human, with human creativity and intuition, they got one that played like a machine, systematically evaluating 200 million possible moves on the chess board per second and winning with brute number-crunching force. As Igor Aleksander, a British AI and neural networks pioneer, explained in his 2000 book, How to Build a Mind:
By the mid-1990s the number of people with some experience of using computers was many orders of magnitude greater than in the 1960s. In the Kasparov defeat they recognized that here was a great triumph for programmers, but not one that may compete with the human intelligence that helps us to lead our lives.
It was an impressive achievement, of course, and a human achievement by the members of the IBM team, but Deep Blue was only intelligent the way your programmable alarm clock is intelligent. Not that losing to a $10 million alarm clock made me feel any better.
....
In what Rasskin-Gutman explains as Moravec's Paradox, in chess, as in so many things, what computers are good at is where humans are weak, and vice versa. This gave me an idea for an experiment. What if instead of human versus machine we played as partners? My brainchild saw the light of day in a match in 1998 in León, Spain, and we called it "Advanced Chess." Each player had a PC at hand running the chess software of his choice during the game. The idea was to create the highest level of chess ever played, a synthesis of the best of man and machine.
Although I had prepared for the unusual format, my match against the Bulgarian Veselin Topalov, until recently the world's number one ranked player, was full of strange sensations. Having a computer program available during play was as disturbing as it was exciting. And being able to access a database of a few million games meant that we didn't have to strain our memories nearly as much in the opening, whose possibilities have been thoroughly catalogued over the years. But since we both had equal access to the same database, the advantage still came down to creating a new idea at some point.
Having a computer partner also meant never having to worry about making a tactical blunder. The computer could project the consequences of each move we considered, pointing out possible outcomes and countermoves we might otherwise have missed. With that taken care of for us, we could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions. Despite access to the "best of both worlds," my games with Topalov were far from perfect. We were playing on the clock and had little time to consult with our silicon assistants. Still, the results were notable. A month earlier I had defeated the Bulgarian in a match of "regular" rapid chess 4–0. Our advanced chess match ended in a 3–3 draw. My advantage in calculating tactics had been nullified by the machine.
This experiment goes unmentioned by Russkin-Gutman, a major omission since it relates so closely to his subject. Even more notable was how the advanced chess experiment continued. In 2005, the online chess-playing site Playchess.com hosted what it called a "freestyle" chess tournament in which anyone could compete in teams with other players or computers. Normally, "anti-cheating" algorithms are employed by online sites to prevent, or at least discourage, players from cheating with computer assistance. (I wonder if these detection algorithms, which employ diagnostic analysis of moves and calculate probabilities, are any less "intelligent" than the playing programs they detect.)
Lured by the substantial prize money, several groups of strong grandmasters working with several computers at the same time entered the competition. At first, the results seemed predictable. The teams of human plus machine dominated even the strongest computers. The chess machine Hydra, which is a chess-specific supercomputer like Deep Blue, was no match for a strong human player using a relatively weak laptop. Human strategic guidance combined with the tactical acuity of a computer was overwhelming.
The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and "coaching" their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.
.....
With the supremacy of the chess machines now apparent and the contest of "Man vs. Machine" a thing of the past, perhaps it is time to return to the goals that made computer chess so attractive to many of the finest minds of the twentieth century. Playing better chess was a problem they wanted to solve, yes, and it has been solved. But there were other goals as well: to develop a program that played chess by thinking like a human, perhaps even by learning the game as a human does. Surely this would be a far more fruitful avenue of investigation than creating, as we are doing, ever-faster algorithms to run on ever-faster hardware.
This is our last chess metaphor, then—a metaphor for how we have discarded innovation and creativity in exchange for a steady supply of marketable products. The dreams of creating an artificial intelligence that would engage in an ancient game symbolic of human thought have been abandoned. Instead, every year we have new chess programs, and new versions of old ones, that are all based on the same basic programming concepts for picking a move by searching through millions of possibilities that were developed in the 1960s and 1970s.
Like so much else in our technology-rich and innovation-poor modern world, chess computing has fallen prey to incrementalism and the demands of the market. Brute-force programs play the best chess, so why bother with anything else? Why waste time and money experimenting with new and innovative ideas when we already know what works? Such thinking should horrify anyone worthy of the name of scientist, but it seems, tragically, to be the norm. Our best minds have gone into financial engineering instead of real engineering, with catastrophic results for both sectors.
...
It illustrates the state of computer chess at the time that it didn't come as much of a surprise when I achieved a perfect 32–0 score, winning every game, although there was an uncomfortable moment. At one point I realized that I was drifting into trouble in a game against one of the "Kasparov" brand models. If this machine scored a win or even a draw, people would be quick to say that I had thrown the game to get PR for the company, so I had to intensify my efforts. Eventually I found a way to trick the machine with a sacrifice it should have refused. From the human perspective, or at least from my perspective, those were the good old days of man vs. machine chess.
Eleven years later I narrowly defeated the supercomputer Deep Blue in a match. Then, in 1997, IBM redoubled its efforts—and doubled Deep Blue's processing power—and I lost the rematch in an event that made headlines around the world. The result was met with astonishment and grief by those who took it as a symbol of mankind's submission before the almighty computer. ("The Brain's Last Stand" read the Newsweek headline.) Others shrugged their shoulders, surprised that humans could still compete at all against the enormous calculating power that, by 1997, sat on just about every desk in the first world.
It was the specialists—the chess players and the programmers and the artificial intelligence enthusiasts—who had a more nuanced appreciation of the result. Grandmasters had already begun to see the implications of the existence of machines that could play—if only, at this point, in a select few types of board configurations—with godlike perfection. The computer chess people were delighted with the conquest of one of the earliest and holiest grails of computer science, in many cases matching the mainstream media's hyperbole. The 2003 book Deep Blue by Monty Newborn was blurbed as follows: "a rare, pivotal watershed beyond all other triumphs: Orville Wright's first flight, NASA's landing on the moon...."
The AI crowd, too, was pleased with the result and the attention, but dismayed by the fact that Deep Blue was hardly what their predecessors had imagined decades earlier when they dreamed of creating a machine to defeat the world chess champion. Instead of a computer that thought and played chess like a human, with human creativity and intuition, they got one that played like a machine, systematically evaluating 200 million possible moves on the chess board per second and winning with brute number-crunching force. As Igor Aleksander, a British AI and neural networks pioneer, explained in his 2000 book, How to Build a Mind:
By the mid-1990s the number of people with some experience of using computers was many orders of magnitude greater than in the 1960s. In the Kasparov defeat they recognized that here was a great triumph for programmers, but not one that may compete with the human intelligence that helps us to lead our lives.
It was an impressive achievement, of course, and a human achievement by the members of the IBM team, but Deep Blue was only intelligent the way your programmable alarm clock is intelligent. Not that losing to a $10 million alarm clock made me feel any better.
....
In what Rasskin-Gutman explains as Moravec's Paradox, in chess, as in so many things, what computers are good at is where humans are weak, and vice versa. This gave me an idea for an experiment. What if instead of human versus machine we played as partners? My brainchild saw the light of day in a match in 1998 in León, Spain, and we called it "Advanced Chess." Each player had a PC at hand running the chess software of his choice during the game. The idea was to create the highest level of chess ever played, a synthesis of the best of man and machine.
Although I had prepared for the unusual format, my match against the Bulgarian Veselin Topalov, until recently the world's number one ranked player, was full of strange sensations. Having a computer program available during play was as disturbing as it was exciting. And being able to access a database of a few million games meant that we didn't have to strain our memories nearly as much in the opening, whose possibilities have been thoroughly catalogued over the years. But since we both had equal access to the same database, the advantage still came down to creating a new idea at some point.
Having a computer partner also meant never having to worry about making a tactical blunder. The computer could project the consequences of each move we considered, pointing out possible outcomes and countermoves we might otherwise have missed. With that taken care of for us, we could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions. Despite access to the "best of both worlds," my games with Topalov were far from perfect. We were playing on the clock and had little time to consult with our silicon assistants. Still, the results were notable. A month earlier I had defeated the Bulgarian in a match of "regular" rapid chess 4–0. Our advanced chess match ended in a 3–3 draw. My advantage in calculating tactics had been nullified by the machine.
This experiment goes unmentioned by Russkin-Gutman, a major omission since it relates so closely to his subject. Even more notable was how the advanced chess experiment continued. In 2005, the online chess-playing site Playchess.com hosted what it called a "freestyle" chess tournament in which anyone could compete in teams with other players or computers. Normally, "anti-cheating" algorithms are employed by online sites to prevent, or at least discourage, players from cheating with computer assistance. (I wonder if these detection algorithms, which employ diagnostic analysis of moves and calculate probabilities, are any less "intelligent" than the playing programs they detect.)
Lured by the substantial prize money, several groups of strong grandmasters working with several computers at the same time entered the competition. At first, the results seemed predictable. The teams of human plus machine dominated even the strongest computers. The chess machine Hydra, which is a chess-specific supercomputer like Deep Blue, was no match for a strong human player using a relatively weak laptop. Human strategic guidance combined with the tactical acuity of a computer was overwhelming.
The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and "coaching" their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.
.....
With the supremacy of the chess machines now apparent and the contest of "Man vs. Machine" a thing of the past, perhaps it is time to return to the goals that made computer chess so attractive to many of the finest minds of the twentieth century. Playing better chess was a problem they wanted to solve, yes, and it has been solved. But there were other goals as well: to develop a program that played chess by thinking like a human, perhaps even by learning the game as a human does. Surely this would be a far more fruitful avenue of investigation than creating, as we are doing, ever-faster algorithms to run on ever-faster hardware.
This is our last chess metaphor, then—a metaphor for how we have discarded innovation and creativity in exchange for a steady supply of marketable products. The dreams of creating an artificial intelligence that would engage in an ancient game symbolic of human thought have been abandoned. Instead, every year we have new chess programs, and new versions of old ones, that are all based on the same basic programming concepts for picking a move by searching through millions of possibilities that were developed in the 1960s and 1970s.
Like so much else in our technology-rich and innovation-poor modern world, chess computing has fallen prey to incrementalism and the demands of the market. Brute-force programs play the best chess, so why bother with anything else? Why waste time and money experimenting with new and innovative ideas when we already know what works? Such thinking should horrify anyone worthy of the name of scientist, but it seems, tragically, to be the norm. Our best minds have gone into financial engineering instead of real engineering, with catastrophic results for both sectors.
...