Garry Kasparov interview Business Insider. Garry. Kasparov. Viktor. KorotayevReuters. Garry Kasparov, one of the greatest chess players of all. IBM. supercomputer Deep Blue. Kasparov won the first match against the computer, 4 2, in. He. recently published a book, Deep. Thinking, about the experience. Kasparov Chess Program' title='Kasparov Chess Program' />Business Insider recently spoke with Kasparov about Deep. Blue, his thoughts on AI, and machine advancements over the past. This interview has been edited for clarity and length. Elena Holodny Whats the biggest misconception. Garry Kasparov AI as a concept is surrounded by. Most of the things we mention we understand. You know, if we say. If we talk about elements of. Kasparov Chess Program' title='Kasparov Chess Program' />Theres no need to go into definition. Now with AI, the moment we mention AI, you should spend a. AI for this very person. And that was one of the purposes of my. And also to understand, what is the nature of human intelligence. Obviously I understand my own limitations. But it is important to. Chess Clubs. Use this page to find uptodate information about current Chess Clubs and other US Chess Affiliates. Upcoming Tournaments. Use this page to learn about. Knights of the South Bronx is a 2005 TV film about a teacher who helps students at a tough innercity school to succeed by teaching them to play chess. A. AI, what do we mean, and what do we expect One of the biggest problems that arise in the beginning of the. Do you mean intelligence as a result of. AI or as a process Because when you look back at my. Ive played with chess computers, now, if we stick. Deep Blue was intelligent because it played. Now, if you look at the process, if you. Deep Blue, this phenomenal speed of 2. And its a big issue. Many people simply dont recognize that. And probably if were talking about. AI and why AI could be. Holodny You draw the distinction between the. Obviously computers are. Kasparov We have different ways of evaluating. For instance, if you try to oversimplify it, in the game of. I have to make my choice. My decision will be based on, very roughly, 1 of calculation. Now the machine will be exactly the opposite. It will be 9. 9. Today, chess programs they are far more sophisticated than Deep. Blue. A free chess app on your mobile is better than Deep Blue. Deep Blue. So maybe its no longer 9. Russian grand master Garry. Kasparov on closed circuit TV at the start of his match in 1. IBM supercomputer Deep Blue in New. ChristensenReuters. And thats why we have to realize that all experiments that are. Go or any other game machines. Chess is. mathematically unsolvable. The number of legal moves is about. But at the end of the day, the machine doesnt have to. The machine has to win the. And to win the game, it just has to make fewer mistakes. Which is not that difficult since humans are humans. So chess, as we found out, could be crunched once the hardware. But again, even if you move from Deep Blue and. Alpha. Go, which is. I would say, looks more. AI, were still staying in the. Its not that machines are impeccable. Looking, for instance, at. I found. out that its not just I who made mistakes, but Deep Blue made. And Im. sure in 2. We should simply accept the fact that the way machines make. If. machines are providing results that we are looking for, you would. And. more likely we should look for the way of combining human skills. And that, I believe, is the future role of. Holodny A chess pieces relative value can. How does a computer. Kasparov The machine doesnt care about. It. looks at immediate returns. So the smart algorithms and very fast. Deep Blue chess computer. Kathy. What you mentioned is still one of the weakest elements, because. But in most cases. And as long as it can see that at move four or five it will get. For example, from the machines perspective, the solution is. You just have to sacrifice the queen. For the. machine, it doesnt matter because it immediately sees that in. But still, for a human player, just to give up a queen for. Humans have some kinds of dead zones. I dont look there. I learned You dont give up the queen. Machines look at everything, so thats another big advantage. And. as I said, the areas where machines are relatively vulnerable. But still, if you bring human plus machine. Holodny Its interesting because thats true of. In neuroradiology, a human is less accurate. Kasparov Yes, that exactly. A machine helps us. We dont have a steady hand. We can. lose all vigilance. We can be distracted by something that is not. But we have intuition. We can feel. certain things. And with a machine you can check whether its. Thats why by bringing the two together, you. Now, what is the most important element of this combinationIts. Let me stick with chess, but Im sure you can look. Sometimes you have a relatively weak. Because with the machine its very important to help. So you dont. need too many of your ideas. Yeah, you have to look, but still. Because at the end. Holodny Its easy to see how humans intuition. Kasparov Again, we are on a very slippery. You know, what is intuition Some of its. Holodny Yeah, Napoleons. Kasparov Yeah, but taking just, you know, pure. I think that if you look for If. I think the. machine will prevail eventually. But there are certain moments. I would bet on intuition especially if we. Holodny Like an early chess program Kasparov Lets talk about 2. Forget about. early chess programs. I reached a conclusion that anything that. Now, the key element. We know how we do it. Because we do. So this is. It needs something at least. You have to bring in something that will. Its like square one. If. theres nothing there, if you cant explain it, thats a problem. One of my optimistic prophecies is based on the assumption that. And the problem for us to explain. We have the purpose, but we still When we look at this. We dont know. So that means. And its a problem for us, some kind of comfort. People say its more like preaching OK, maybe. Because, as I mentioned in the book and all my lectures, is that. Hollywood The Terminator, the Skynet, The Matrix. Its. I think its just a way, way, way, way in. Is it going to happen I dont know. For me, these. Frankly. I dont care. Laughs. Holodny How does it feel playing against AI. For example, you versus Deep Blue. Kasparov That was quite an experience, and Ive. In the book, I started. Hamburg, in 1. 98. Im still trying. I. I left chess in 2. So I. didnt just witness that but I was an active part of this. And, in fact, after matches with Deep Blue, I played two. German program and an. Download Software Sons Of Liberty Riders Back Patch. Israeli program in 2. To sum up objectively, I think I was still stronger maybe the. If IBM didnt retire the machine and we played, I. I had a chance of winning. But from the historical. I can go even further saying that. Philadelphia match 1. I won eventually in. One year, two years, five years but we were there. We. were on that road. So that eventually the machine will be able to. So it was clear that the machine had reached the. Shannon, known as the father of information. Wikimedia. But going back to this match, Im leaning toward blessing. So. even if its not one of the most comfortable parts, its still. And I think, you know, whats happened there is we. Its interesting that the greatest minds of computer science, the. Alan Turing and Claude Shannon and Norbert. Wiener, they all looked at chess as the ultimate test. So they. thought, Oh, if a machine can play chess, and beat. AI era. With all due respect, they were. Its an important step forward, but were still, still far. I think its the best lesson from this match. And Im always saying that its for us to find new. So, somehow, AI is playing an important role of breaking up the. The Chess Master and the Computer by Garry Kasparovby Diego Rasskin Gutman, translated from the Spanish by Deborah Klosky. MIT Press, 2. 05 pp., 2. Steve HondaAFPGetty Images. Garry Kasparov during his rematch against the IBM supercomputer Deep Blue, 1. In 1. 98. 5, 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 didnt come as much of a surprise when I achieved a perfect 3. 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. Eleven years later I narrowly defeated the supercomputer Deep Blue in a match. Then, in 1. 99. 7, IBM redoubled its effortsand doubled Deep Blues processing powerand 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 mankinds submission before the almighty computer. The Brains 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 1. It was the specialiststhe chess players and the programmers and the artificial intelligence enthusiastswho had a more nuanced appreciation of the result. Grandmasters had already begun to see the implications of the existence of machines that could playif only, at this point, in a select few types of board configurationswith 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 medias hyperbole. The 2. 00. 3 book Deep Blue by Monty Newborn was blurbed as follows a rare, pivotal watershed beyond all other triumphs Orville Wrights first flight, NASAs 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 2. As Igor Aleksander, a British AI and neural networks pioneer, explained in his 2. How to Build a Mind. By the mid 1. 99. 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 1. My hopes for a return match with Deep Blue were dashed, unfortunately. IBM had the publicity it wanted and quickly shut down the project. Other chess computing projects around the world also lost their sponsorship. Though I would have liked my chances in a rematch in 1. I were better prepared, it was clear then that computer superiority over humans in chess had always been just a matter of time. Today, for 5. 0 you can buy a home PC program that will crush most grandmasters. In 2. 00. 3, I played serious matches against two of these programs running on commercially available multiprocessor serversand, of course, I was playing just one game at a timeand in both cases the score ended in a tie with a win apiece and several draws. Inevitable or not, no one understood all the ramifications of having a super grandmaster on your laptop, especially what this would mean for professional chess. There were many doomsday scenarios about people losing interest in chess with the rise of the machines, especially after my loss to Deep Blue. Some replied to this with variations on the theme of how we still hold footraces despite cars and bicycles going much faster, a spurious analogy since cars do not help humans run faster while chess computers undoubtedly have an effect on the quality of human chess. Another group postulated that the game would be solved, i. Or perhaps it would prove that a game of chess played in the best possible way always ends in a draw. Perhaps a real version of HAL 9. These gloomy predictions have not come true, nor will they ever come to pass. Chess is far too complex to be definitively solved with any technology we can conceive of today. However, our looked down upon cousin, checkers, or draughts, suffered this fate quite recently thanks to the work of Jonathan Schaeffer at the University of Alberta and his unbeatable program Chinook. The number of legal chess positions is 1. Authors have attempted various ways to convey this immensity, usually based on one of the few fields to regularly employ such exponents, astronomy. In his book Chess Metaphors, Diego Rasskin Gutman points out that a player looking eight moves ahead is already presented with as many possible games as there are stars in the galaxy. Another staple, a variation of which is also used by Rasskin Gutman, is to say there are more possible chess games than the number of atoms in the universe. All of these comparisons impress upon the casual observer why brute force computer calculation cant solve this ancient board game. They are also handy, and I am not above doing this myself, for impressing people with how complicated chess is, if only in a largely irrelevant mathematical way. This astronomical scale is not at all irrelevant to chess programmers. Theyve known from the beginning that solving the gamecreating a provably unbeatable programwas not possible with the computer power available, and that effective shortcuts would have to be found. In fact, the first chess program put into practice was designed by legendary British mathematician Alan Turing in 1. He processed the algorithm on pieces of paper and this paper machine played a competent game. Rasskin Gutman covers this well traveled territory in a book that achieves its goal of being an overview of overviews, if little else. The history of the study of brain function is covered in the first chapter, tempting the reader to skip ahead. You might recall axons and dendrites from high school biology class. We also learn about cholinergic and aminergic systems and many other things that are not found by my computers artificially intelligent English spell checking systemor referenced again by the author. Then its on to similarly concise, if inconclusive, surveys of artificial intelligence, chess computers, and how humans play chess. There have been many unintended consequences, both positive and negative, of the rapid proliferation of powerful chess software. Kids love computers and take to them naturally, so its no surprise that the same is true of the combination of chess and computers.