This site may earn affiliate commissions from the links on this page.A computing cluster using only 24 machines identical to the Deep Blitz machine (dual processor/dual core Opteron x64 processors running at 2.2GHz) would surpass Deep Blue’s performance, but currently available microcomputer chess software does not run on computing clusters or on a grid. At the moment, the only multithreaded commercial chess programs are Deep Fritz and Deep Shredder. Deep Fritz 9 Multiprocessor Edition will ship from ChessBase in the second quarter of 2006 but it’s unlikely that chess-engine optimizations or incremental performance improvements will make a significant difference in terms of chess positions per second. Either additional processors or specialized chess chips (or both) are necessary to catch up to Deep Blue.Setting aside hardware issues and brute force benchmarks, chess software has improved in the past few years. Evaluating the games from the 1997 Kasparov-versus–Deep Blue match using the Deep Blitz machine shows that Deep Fritz and Deep Shredder consistently find very strong moves for either player within chess tournament time controls and generally do not make the moves considered to have been mistakes in post-game analysis of the historic match. Despite its vastly inferior brute force, the Deep Blitz machine could already be a match for Deep Blue because of improvements in chess software. Deep Fritz is able to evaluate lines of play to a similar depth because it successfully narrows its search only to the strongest lines of play.The data suggest that Deep Blue spent a lot of time evaluating bad moves but overcame this weakness through brute force.
In a match between Deep Blue and the Deep Blitz machine running Deep Fritz or Deep Shredder, it seems unclear which machine would win. Obviously, Kasparov did not evaluate 200 million chess positions per second when he defeated Deep Blue in game 1 of the 1997 match, thus the 200 million positions per second number is not a requirement to play chess at the word championship level.
It seems likely that Deep Fritz, which is more efficient at filtering out weak moves, is a far more ‘intelligent’ chess program compared with Deep Blue’s software. Setting aside the improvements in chess software, the goal of challenging Deep Blue using a PC or a small cluster of PCs, if it has not already been achieved, is definitely within reach. A cluster of machines or a future system similar to the Deep Blitz machine (for example, with quad 64-bit multi-core processors on the motherboard and 8 or more cores per socket running at 4.0GHz or faster) would obviously surpass Deep Blue in terms of brute force. It’s only a matter of time; perhaps another 5 years from a hardware perspective.In terms of software, there is a Linux-based Open Source project, that aims to develop a massively scalable chess program that runs on a cluster of computers.
A program like ChessBrain running on a cluster of machines like the Deep Blitz machine would be a logical step toward surpassing Deep Blue. A project of this kind using ChessBrain would cost roughly $500,000 dollars today—less than 1% of the cost of IBM’s Deep Blue project. In another 5 years, the cost will be a fraction of that number. In the mean time, Deep Blue’s baby brother, Deep Blitz, plays a “pretty good” game of chess. Deep Blitz Hardware ComponentsComponentDescriptionManufacturerMotherboardTyan Thunder K8SE (S2892)TyanCPU2 ea. 2.2GHz 64-bit dual-core AMD Opteron (model 275) microprocessorsAMDMemory4 GB Kingston HyperX DDR 400 ECC SDRAM (2 ea.
KRX3200AK2/2GB)KingstonCaseSilverStone Temjin III Nimitz server case (SSTTJ03)SilverStonePower supply520W OCZ PowerStream power supply (OCZ-520ADJ)OCZVideo cardSapphire ATI Radeon X1800 CrossFire PCI-E x16 with 512MB GDDR3 memorySapphire (ATI)Audio cardCreative Audigy 2 ZSCreativeCD/DVD ROMSony DRU-810A dual-layer 8.5 GB DVD driveSonyRAID controllerOn-board Nvidia nForce4 chipset SATA RAID controllerNvidiaHard drives4 ea. Seagate Barracuda 160 GB 7200.7 RPM SATA/150 hard drives (ST3160827AS)Seagate.
Deep Blue Chess Match
Just over 19 years ago, a milestone in the world of AI was achieved when IBM’s supercomputer Deep Blue defeated Garry Kasparov. Until then, he was the undefeated world Chess champion – probably the greatest human player of all time.
Garry Kasparov in The Ultimate Blitz Challenge, St Louis (2016). Imagen:This was a momentous event in AI’s brief history. Computer chess programs had been playing good chess since the 1970’s, and had improved to the point where their level of play would beat the vast majority of the population. I myself recall buying a chess program in the early 1980’s which offered 6 levels of play from beginner to advanced. Even then, I had difficulty beating the machine above level 3. By the time Kasparov played Deep Blue, the quality of chess playing software was improving rapidly.
But the step up to beating a grand master was viewed by most pundits – including Kasparov himself – as very unlikely.The match took place in New York in May 1997 and involved the best of six games. Kasparov won the first game but was unexpectedly defeated in the second game. Kasparov was clearly rattled by this defeat and, during a press conference the following day, he accused Deep Blue of cheating. He rationised this by claiming it displayed unpredictable behaviour which he thought had been due to tampering during the game by the IBM programming team. The rules stipulated that the programmers could alter the program between games but not during a game. The IBM team caught Kasparov off-guard because he believed that computer chess programs, although exessively fast and computationally flawless, would not claim the scalp of a grand master because of their predictable perfunctory behaviour. After Kasparov defeated Deep Blue in the first game, the IBM team generated more randomised unpredicatability into the software.
It worked, and Deep Blue went on to win the match.Up until this defeat Kasparov had been, with some justification, quite derisory about the limits of machine intelligence. For Deep Blue essentially used AI techniques which at that time involved “brute force” searching to win at chess.
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Brute force searching was a commonly used paradigm in the early days of AI that would attempt to suceed by overwhelming opponents with computer power by searching rapidly through millions of combinations of moves – in the case of Deep Blue, more than 200 million possible moves were analysed per second. The search space (i.e., the possible moves) would usually be reduced with the use of pruning methods. This would be important because, in chess tournaments, players are normally limited to a time of three minutes per move. However, no human being could ever get anywhere near analysing 200 million possible moves in a lifetime, let alone a second. But that did not matter to Kasparov at the time, because he believed that human intelligence and years of experience empowered him with intuitive insights that were such that he did not need to analyse.
Indeed, when he was once asked how many moves he analyses per second, he declared: ” less than one”. IMB Deep Blue computer Image:This means that the battle lines were broadly drawn, at that time, between the superior computational power and accuracy of the dumb machine and the creative, insightful genius, of the human grand master.
But 19 years on, the AI world has changed considerably. Today, as Kasparov himself admits: “A decent laptop running a free chess program would crush Deep Blue and any human grandmaster. The jump from chess machines being predictable and weak to terrifyingly strong took just a dozen years”. Kasparov appears to have become a convert and now recognes the insights and discoveries computer chess have made of benefit to human chess players.Why is he now saying this? Because computer hardware continues relentlessly to get faster but also AI programs no longer rely on brute force search algorithms as they did in the early days of AI. Nowadays, the AI in language translation programs or driverless cars and advanced chess programs use techniques – such as genetic algorithms and neural networks – that are more akin to the way in which human intelligence works.
What these techniques offer that previous techniques did not is both the ability to carry out pattern matching better mimicking human thinking, and also the ability to learn. Good human chess players, like experts in other subject domains, use pattern recognition skills built from experience, and AI techniques are now becoming good at pattern matching – something which was thought unlikely by many until fairly recently. Learning techniques can improve the chess playing software and take it to new levels.It is said that one of the key milestones in human evolution was the time, estimated to be about 1 million years ago, when our primate ancestors learned by observing others at work. It took billions of years of biological evolution to reach that point.
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Yet, many now believe that AI programs will achieve the same level of learning capabilities as humans in the next few decades. This is truly astonishing and begs the question where is AI taking us?
I will discuss this further in the next article. By Keith Darlington.
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Wrap your PGNs with pgn and /pgn (without the spaces) to allow users to see the game as an interactive chess board.Chess Spoiler format for problem answers etc.,!Spoiler text! Great question!Unfortunately, it doesn't work like that. The actual deep blue machine was shut down and dismantled by IBM pretty quickly. Kasparov publicly accused IBM of cheating and demanded they publish logs, and they responding by dismantling the machine and refusing to give over the logs (they are now available online, but IBM refused to publish them for years)Also remember it didn't run on a PC, but on custom hardware designed to play chess, so to run it you'd have to simulate the entire machine in software. Not sure if they ever sold the name/brand to some other chess program, but the actual deep blue that Kasparov played is dead and gone. Great question. Computers are still weaker than humans in some aspects of chess, and in the 90s that difference was much more pronounced.
In a closed position, where the center is locked and each side needs to find a long term plan to break through, engines are prone to shuffle about randomly. In addition, engines used to be very materialistic and grab pawns all the time, underestimating the resulting attack.The theory that some people put forth is that there was a strong player (around international master level) hidden behind the scenes. When deep blue suggested a move that looked like a typical engine mistake, the IM would throw it out and deep blue would come up with another move.
On May 11, 1997, an IBM computer called IBM® Deep Blue® beat the world chess champion after a six-game match: two wins for IBM, one for the champion and three draws. The match lasted several days and received massive media coverage around the world. It was the classic plot line of man vs. Behind the contest, however, was important computer science, pushing forward the ability of computers to handle the kinds of complex calculations needed to help discover new medical drugs; do the broad financial modeling needed to identify trends and do risk analysis; handle large database searches; and perform massive calculations needed in many fields of science. Since the emergence of artificial intelligence and the first computers in the late 1940s, computer scientists compared the performance of these “giant brains” with human minds, and gravitated to chess as a way of testing the calculating abilities of computers. The game is a collection of challenging problems for minds and machines, but has simple rules, and so is perfect for such experiments.Over the years, many computers took on many chess masters, and the computers lost.IBM computer scientists had been interested in chess computing since the early 1950s.
In 1985, a graduate student at Carnegie Mellon University, Feng-hsiung Hsu, began working on his dissertation project: a chess playing machine he called ChipTest. A classmate of his, Murray Campbell, worked on the project, too, and in 1989, both were hired to work at IBM Research. There, they continued their work with the help of other computer scientists, including Joe Hoane, Jerry Brody and C.
The team named the project Deep Blue. The human chess champion won in 1996 against an earlier version of Deep Blue; the 1997 match was billed as a “rematch.”The champion and computer met at the Equitable Center in New York, with cameras running, press in attendance and millions watching the outcome. The odds of Deep Blue winning were not certain, but the science was solid. The IBMers knew their machine could explore up to 200 million possible chess positions per second. The chess grandmaster won the first game, Deep Blue took the next one, and the two players drew the three following games.
Deep Blue Chess Software Download
Game 6 ended the match with a crushing defeat of the champion by Deep Blue.The match’s outcome made headlines worldwide, and helped a broad audience better understand high-powered computing. The 1997 match took place not on a standard stage, but rather in a small television studio. The audience watched the match on television screens in a basement theater in the building, several floors below where the match was actually held. The theater seated about 500 people, and was sold out for each of the six games. The media attention given to Deep Blue resulted in more than three billion impressions around the world.Deep Blue had an impact on computing in many different industries. It was programmed to solve the complex, strategic game of chess, so it enabled researchers to explore and understand the limits of massively parallel processing. This research gave developers insight into ways they could design a computer to tackle complex problems in other fields, using deep knowledge to analyze a higher number of possible solutions.
Deep Blue, computer -playing system designed by in the early 1990s. As the successor to Chiptest and, earlier purpose-built chess computers, Deep Blue was designed to succeed where all others had failed. In 1996 it made history by defeating Russian grandmaster in one of their six games—the first time a computer had won a game against a world champion under tournament conditions. In the 1997 rematch, it won the deciding sixth game in only 19 moves; its 3.5–2.5 victory (it won two games and had three draws) marked the first time a current world champion had lost a match to a computer under tournament conditions. In its final configuration, the IBM RS6000/SP computer used 256 processors working in tandem, with an ability to evaluate 200 million chess positions per second.