Chess is one of the world's most popular games. Its popularity and complexity make it an interesting research domain for artificial intelligence. The number of board positions we can get to from the initial board state is larger than the number of atoms in the universe! Chess playing machines have been the subject of human interest for hundreds of years, but only on the last few decades have they been able to compete with (and beat) the world champions. Chess programs now have their own tournaments.
A computer screen is photographed February 16, 1996 at IBM's headquarters in Armonk, New York, during IBM's supercomputer Deep Blue' s matches against world chess champion Garry Kasparov. The word "bot" is a name given to artificial intelligence (AI) that takes the place of player characters in online multiplayer video games. Some of the earliest examples include Perfect Dark on the Nintendo 64 system, which included the feature as a means of bypassing player limitations on such pre-Internet enabled consoles. AI has been a feature of video games since their inception way back in 1947 with one of the most significant examples of inclusion being with Deep Blue, a chess computer created by IBM which is notable for its ability to best the greatest minds in chess, including Garry Kasparov. However, AI is a concept that has somewhat been flipped on its head in recent years, as ground-breaking innovations such as machine learning and Internet of Things (IOT) have become vital instrumentalities in the corporate world.
Despite losing at chess to the IBM Deep Blue computer more than 20 years ago, Garry Kasparov is a big believer in artificial intelligence. The former world chess champion is now an author and speaker who is trying to counter some of the more alarmist beliefs over the rise of AI technologies, typically exemplified in Hollywood movies in which robots rise against their human creators. Speaking at the Train AI conference on Thursday in San Francisco, Kasparov explained how humanity has long considered people's performance in playing a game of chess as a metric of intelligence. "People looked at it as an opportunity to go deep in the human mind," he said of chess. That's why when Kasparov lost to Deep Blue in 1997 in a rematch from a prior match he won in 1996 -- which, he likes to note, "nobody remembers" -- people considered it a "watershed moment" for computer science.
Garry Kasparov, a former Soviet world chess champion and one of the greatest players of all time, has changed his tune about AI since he was beaten by IBM's Deep Blue. During a talk at the Train AI conference in San Francisco on Thursday, Kasparov traced the steps that convinced him about how humans and machines might one day work together to create an "augmented intelligence". He's had a lot of time to contemplate the rise of machines. Over 20 years ago, at the height of his career as the world chess champion, he entered a competition to play chess against a supercomputer. "The day machines would beat the strongest human player had to be the dawn of AI.
We're not being replaced by AI. My chess loss in 1997 to IBM supercomputer Deep Blue was a victory for its human creators and mankind, not triumph of machine over man. In the same way, machine-generated insight adds to ours, extending our intelligence the way a telescope extends our vision. We aren't close to creating machines that think for themselves, with the awareness and self-determination that implies. Our machines are still entirely dependent on us to define every aspect of their capabilities and purpose, even as they master increasingly sophisticated tasks.
The area of computation called artificial intelligence (AI) is falsified by describing a previous 1972 falsification of AI by British applied mathematician James Lighthill. It is explained how Lighthill's arguments continue to apply to current AI. It is argued that AI should use the Popperian scientific method in which it is the duty of every scientist to attempt to falsify theories and if theories are falsified to replace or modify them. The paper describes the Popperian method in detail and discusses Paul Nurse's application of the method to cell biology that also involves questions of mechanism and behavior. Arguments used by Lighthill in his original 1972 report that falsified AI are discussed. The Lighthill arguments are then shown to apply to current AI. The argument uses recent scholarship to explain Lighthill's assumptions and to show how the arguments based on those assumptions continue to falsify modern AI. An important focus of the argument involves Hilbert's philosophical programme that defined knowledge and truth as provable formal sentences. Current AI takes the Hilbert programme as dogma beyond criticism while Lighthill as a mid 20th century applied mathematician had abandoned it. The paper uses recent scholarship to explain John von Neumann's criticism of AI that I claim was assumed by Lighthill. The paper discusses computer chess programs to show Lighthill's combinatorial explosion still applies to AI but not humans. An argument showing that Turing Machines (TM) are not the correct description of computation is given. The paper concludes by advocating studying computation as Peter Naur's Dataology.
Futurist Arthur C. Clarke wrote, "Any sufficiently advanced technology is indistinguishable from magic." The magic of software (giving data and rules to get answers) is often confused with the magic of machine learning (giving data and answers to get rules) but it is machine learning not software that is transforming the world of computer chess. So far, computer chess programs codified the actions of the best human players and inevitably pivoted around the strategy of "material", wherein the number and value of pieces mattered most. Reports suggest AlphaZero taught itself chess from scratch in just four hours by playing against itself and rejected human rules developed over centuries. As it started with only the basic rules, researchers suggest that its lack of knowledge of human chess history may have enabled AlphaZero to see the game in a fresh way.
People are concerned about robots. Ever since a computer system defeated chess champion Gary Kasparov 20 years ago, public perceptions of progress in artificial intelligence (AI) research have been defined in terms of high-profile competitions pitting human against thinking machine. Anxiety is high about what the ultimate consequences could be.
Carnegie-Mellon University's Hitech chess computer scored 5-1 in the National Open Chess Championships held in Chicago March 18-20. The Championship Section in which Hitech competed, had 380 entries. The Championship Section in which Hitech competed, had 380 entries. There was a six-way tie for first with 5.5 points between: International Grandmaster Mikhail Tal (a former world champion), International Grandmaster Sergey Kudrin, FIDE Master Michael Brooks, International Master James Rizzitano, International Master Calvin Blocker, and International Grandmaster Leonid Shamkovich. Tied for seventh with 5 points were: National Master Hitech, International Grandmaster Maxim Dlugy, International Grandmaster Walter Browne, International Grandmaster Arthur Bisguier, and nine others.
Deep Blue beat world chess champion Gary Kasparov in the final game of a tied, six-game match last May 11. Kasparov had beaten the machine in an earlier match held in February 1996. The Fredkin Prize was awarded under the auspices of AAAI; funds had been held in trust at Carnegie Mellon University. The Fredkin Prize was originally established at Carnegie Mellon University 17 years ago by Massachusetts Institute of Technology Computer Science Professor Edward Fredkin to encourage continued research progress in computer chess. The first award of $5,000 was given to two scientists from Bell Laboratories who in 1981 developed the first chess machine to achieve master status.