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.
The game of chess is one of the world's most popular two-player board games. I often times find myself wanting to play even when no one is around to play. One solution to this problem is to play chess on a computer or mobile device against. However, many people would agree with me in thinking that playing a virtual game of chess is a completely different experience than playing a physical game of chess. For this reason, I intend to use this project as an opportunity to build a 6 degree of freedom robotic arm that will take the place of an opponent in a physical game of Chess.
Chess is a complicated game. It's a game of strategy between two opponents, but with no hidden information and all of the potential moves known by both players at the outset. With each turn, players communicate their intent and try to anticipate the possible countermoves. The ability to envision several moves in advance is a recipe for victory, and one that mathematicians and logicians have long found intriguing. Despite some early mechanical chess-playing machines--and at least one chess-playing hoax--mechanized chess play remained hypothetical until the advent of digital computing.
In 1997 when Deep Blue, a supercomputer, beat the then chess champion, Garry Kasparov, we all were taken aback. That was more than 20 years ago and most of us did not even know that computers like that even existed. In late 2017, AlphaZero taught itself how to play chess under just four hours and beat the world's then best chess-playing computer program. Remember, AlphaZero, the game-playing AI created by DeepMind, was not taught any domain knowledge but the rules of the game. Such is the power of machines to learn and improvise and industries across the world are tapping a machine's ability to learn and improve from its experience without being explicitly programmed.
With interest soaring in machine learning and its role in all kinds of games, chess will be in the spotlight at the prestigious MIT Sloan Sports Analytics Conference this year, organizers announced today. The chess program is scheduled for Saturday, March 2. Chess.com's The panel places chess at the famous Sloan conference, which has deeply influenced the landscape of sports and social science analytics in recent years. The session is called Chess AI Transformation: How Self Learning AI Taught Chess Computers (and Humans) a Lesson. "The game of chess continues to act as a barometer for the leading edge of artificial intelligence, and [...] artificial intelligence continues to fundamentally transform the game at the highest levels," according to the conference promotional materials.
This article is reproduced with kind permission of Spiegel Online, where it first appeared. The author was told to make the series personal, describe the development of chess programming not as an academic treatise but as a personal story of how he had experienced it. For some ChessBase readers a number of the passages will be familiar, since the stories have been told before on our pages. For others this can serve as a roadmap through one of the great scientific endeavors of our time. It was the mid 1990s.
In March 2015, as they prepared to cast their votes in a landmark presidential election, Nigerians found themselves facing a choice between the devil and the deep blue sea: Goodluck Jonathan, the then-incumbent whose administration was corrupt and largely inept; and Muhammadu Buhari, an erstwhile dictator known for his ethnoreligious biases. Eventually, the voters decided Buhari - who had branded himself "a reformed democrat" and promised to fight corruption - is the lesser of the two evils and chose him as their next president. After the election, Jonathan willingly conceded his defeat to Buhari, becoming the first sitting president in Nigeria to do so. Despite Buhari's flimsy democratic credentials, this peaceful transfer of power, coupled with the new president's initial successes in the fight against corruption, convinced many Nigerians that they had made the right choice. For a short while, many Nigerians believed that they may not be forced to choose "the lesser of the two evils" in future elections.
Four new malware strains are created every second, and the banking industry is almost 300 times as likely to get attacked by malware as other types of businesses, according to Nayeem Islam, CEO of Blue Hexagon. That's why his deep-learning cybersecurity startup, which has been in stealth mode for a year and a half and officially launched Tuesday, is making financial services one of the primary industries it serves. The company has received $31 million in funding from the venture capital firms Benchmark and Altimeter Capital. Heffernan Insurance is its first public customer. Blue Hexagon uses self-learning technology to catch network threats, Islam said.
For several decades, various types of artificial intelligence have been facing off with people in highly competitive games and then quickly destroying their human competition. AI long ago mastered chess, the Chinese board game Go and even the Rubik's cube, which it managed to solve in just 0.38 seconds. Now machines have a new game that will allow them to humiliate humans: Jenga, the popular game ---- and source of melodramatic 1980s commercials ---- in which players strategically remove pieces from an increasingly unstable tower of 54 blocks, placing each one on top until the entire structure collapses. A newly released video from MIT shows a robot developed by the school's engineers playing the game with surprising precision. The machine is quipped with a soft-pronged gripper, a force-sensing wrist cuff and an external camera, allowing the robot to perceive the tower's vulnerabilities the way a human might, according to Alberto Rodriguez, the Walter Henry Gale career development assistant professor in the Department of Mechanical Engineering at MIT. "Unlike in more purely cognitive tasks or games such as chess or Go, playing the game of Jenga also requires mastery of physical skills such as probing, pushing, pulling, placing, and aligning pieces," Rodriguez said in a statement released by the school.
Twenty years ago IBM's Deep Blue computer stunned the world by becoming the first machine to beat a reigning world chess champion in a six-game match. The supercomputer's success against an incredulous Garry Kasparov sparked controversy over how a machine had managed to outmaneuver a grand master, and incited accusations--by Kasparov and others--that the company had cheated its way to victory. The reality of what transpired in the months and years leading up to that fateful match in May 1997, however, was actually more evolutionary than revolutionary--a Rocky Balboa–like rise filled with intellectual sparring matches, painstaking progress and a defeat in Philadelphia that ultimately set the stage for a triumphant rematch. Computer scientists had for decades viewed chess as a meter stick for artificial intelligence. Chess-playing calculators emerged in the late 1970s but it would be another decade before a team of Carnegie Mellon University graduate students built the first computer--called Deep Thought--to beat a grand master in a regular tournament game.