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What do John Wayne, Stephen Hawking, Queen Elizabeth I, Julia Roberts, Ray Charles, Marilyn Monroe and Che Guevara all have in common?

12/31/2016

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The 'Queen of Chess' who defeated Kasparov

12/31/2016

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10 February 2016 Last updated at 00:08 GMT
Hungarian chess champion Judit Polgar started playing chess from a very young age and almost immediately it became clear she had a special talent for the sport.
As a young girl, she soon swapped playing people of her own age to experienced adult professionals around the world.
Initially, Polgar was dismissed by many in the sport as not up to the challenge of playing against men.
Then world champion Garry Kasparov was the most renowned player to question whether a woman could beat a man.
However, during the 2002 Russia versus the Rest of the World tournament, Polgar got the ultimate revenge by beating Kasparov. She was the first woman to do so.
Judit Polgar spoke to Witness about their rivalry and that historic moment in the sport of chess.

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When Computers Started Beating Chess Champions

12/31/2016

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http://www.theatlantic.com/technology/archive/2016/02/when-computers-started-beating-chess-champions/462216/
 Marina Koren Feb 10, 2016

On this day 20 years ago, a machine defeated a sitting world champion for the first time.
Shutterstock

There was a time, not long ago, when computers—mere assemblages of silicon and wire and plastic that can fly planes, drive cars, translate languages, and keep failing hearts beating—could really, truly still surprise us.

One such moment came on February 10, 1996, at a convention center in Philadelphia. Two chess players met for the first of six tournament matches. Garry Kasparov, the Soviet grandmaster, was the World Chess champion, famous for his aggressive and uncompromising style of play. Deep Blue was a 6-foot-5-inch, 2,800-pound supercomputer designed by a team of IBM scientists.

“There was no way that this tin box was going to defeat a reigning world champion,” says Maurice Ashley, an American grand chessmaster who provided live commentary for the game that day.

Kasparov thought so, too. He’d previously scoffed at the suggestion that a chess-playing computer might defeat a grandmaster before the year 2000, which, back then, probably seemed pretty ridiculous to most people. Personal computers were just over a decade old, and looked liked this. Commercial companies had begun providing Internet access to the general public only the year before. Chess required guile, wit, and foresight—distinctly human traits—and a hunk of hardware, the chess community thought, could not replicate all that—at least not well enough to beat Kasparov.

But the tin box won that game, becoming the first computer to defeat a sitting world chess champion.

Chess players and computer scientists alike were stunned. Computers were by then known for doing some things better than humans could, like solving complex math problems or processing employees’ paychecks. “But everybody knew that chess required intelligence to play well, so to see that a computer could do this and compete with the best player in the world—that was sort of a wakeup call,” says Murray Campbell, one of the IBM computer scientists who developed Deep Blue, and a competitive chess player himself. “It was a sign that a lot more was coming.”

The concept of chess-playing machines dates back centuries. One of the first iterations was rather dishonest: an automaton created by Wolfgang von Kempelen, a Hungarian inventor, in the 1760s only managed to win because the human player hidden inside was pulling levers to move pieces across the board. It took humans until the 1950s to program machines to observe the rules of chess. By the 1980s, computers could conduct basic searches of potential moves and strategies, but at considerably quick speeds, searching several thousands positions per second. They started competing against skilled human players—and winning. In 1987, Deep Thought, the precursor to Deep Blue, defeated British chessmaster David Levy.

“Deep Thought sees far but notices little, remembers everything but learns nothing, neither erring egregiously nor rising above its normal strength,” the IBM scientists wrote in 1990. “Even so, it sometimes produces insights that are overlooked by even top grandmasters.”

Deep Blue was considerably more advanced. At its core, the computer was built to solve complex numerical problems. In front of a chess board, Deep Blue, equipped with data from hundreds of existing master games, would scan the board for features it recognized. Like a human player, the computer thought ahead, exploring potential moves in terms of sequences, envisioning future positions. It numerically rated the moves as it went, finally making the one that came out with the highest rating—the “best” move. Deep Blue was capable of evaluating 100 million positions per second.

Kasparov went into the historic game in 1996 feeling confident, but it soon became clear Deep Blue was a tougher competitor than he’d expected. Kasparov, already known for being an animated player, was visibly frustrated during the game, often shaking his head, says Jeffrey Popyack, a computer science professor at Drexel University who was in the room. At one point, Kasparov spent 27 minutes deliberating before moving his queen. “The thing that really sticks with me now was just the anguish that Kasparov was going through,” Popyack recalls.

Toward the end of game, Kasparov and Deep Blue were like “two sumo wrestlers battling one another at the edge of a high cliff,” as Monty Newborn, chairman of the computer chess committee for the Association of Computing Machines, once put it. Kasparov was mounting an aggressive attack on Deep Blue’s king when the machine made an unusual move—going after a pawn across the board—that suggested the machine was unaware it was in trouble. (“It would be kind of like your house was burning down and you decided to go grocery shopping,” Ashley, the American grandmaster, said.) Turns out the computer had calculated that Kasparov’s move—a bold bluff that would have intimidated a human player—wasn’t going to work. The world champion, visibly distraught, resigned a few moves later.

Modern, game-playing artificial intelligence is, well, even scarier. In 2011, Watson, an IBM super computer capable of answering open-ended questions posed in human language defeated Ken Jennings on Jeopardy! Last month, a computing system developed by Google researchers bested the top human player of Go, a complex 2,500-year-old game that depends heavily on intuition and strategy. (Popyack points out that, despite all that, computers are still not very good at programming other computers.)

Human players are successful if they can spot their opponents’ blind spots, and supercomputers are built to find even the smallest of errors and exploit them. “It’s never going to get tired, and it’s never going to get overconfident, and it’s just going to kill you,” Ashley said. “That’s the difference now. It’s like playing the Terminator.”

Kasparov rebounded in the second game against Deep Blue, and went on to win the whole six-game series. But the scales had been tipped. And in a subsequent matchup in 1997, Deep Blue triumphed. Humans were no longer winning the battle between man and machine.

“It’s a really dangerous business to say, ‘computers will never,’ and then say something after that,” Campbell says.

When Computers Started Beating Chess Champions

On this day 20 years ago, a machine defeated a sitting world champion for the first time.
Shutterstock

There was a time, not long ago, when computers—mere assemblages of silicon and wire and plastic that can fly planes, drive cars, translate languages, and keep failing hearts beating—could really, truly still surprise us.

One such moment came on February 10, 1996, at a convention center in Philadelphia. Two chess players met for the first of six tournament matches. Garry Kasparov, the Soviet grandmaster, was the World Chess champion, famous for his aggressive and uncompromising style of play. Deep Blue was a 6-foot-5-inch, 2,800-pound supercomputer designed by a team of IBM scientists.

“There was no way that this tin box was going to defeat a reigning world champion,” says Maurice Ashley, an American grand chessmaster who provided live commentary for the game that day.

Kasparov thought so, too. He’d previously scoffed at the suggestion that a chess-playing computer might defeat a grandmaster before the year 2000, which, back then, probably seemed pretty ridiculous to most people. Personal computers were just over a decade old, and looked liked this. Commercial companies had begun providing Internet access to the general public only the year before. Chess required guile, wit, and foresight—distinctly human traits—and a hunk of hardware, the chess community thought, could not replicate all that—at least not well enough to beat Kasparov.

But the tin box won that game, becoming the first computer to defeat a sitting world chess champion.

Chess players and computer scientists alike were stunned. Computers were by then known for doing some things better than humans could, like solving complex math problems or processing employees’ paychecks. “But everybody knew that chess required intelligence to play well, so to see that a computer could do this and compete with the best player in the world—that was sort of a wakeup call,” says Murray Campbell, one of the IBM computer scientists who developed Deep Blue, and a competitive chess player himself. “It was a sign that a lot more was coming.”

The concept of chess-playing machines dates back centuries. One of the first iterations was rather dishonest: an automaton created by Wolfgang von Kempelen, a Hungarian inventor, in the 1760s only managed to win because the human player hidden inside was pulling levers to move pieces across the board. It took humans until the 1950s to program machines to observe the rules of chess. By the 1980s, computers could conduct basic searches of potential moves and strategies, but at considerably quick speeds, searching several thousands positions per second. They started competing against skilled human players—and winning. In 1987, Deep Thought, the precursor to Deep Blue, defeated British chessmaster David Levy.

“Deep Thought sees far but notices little, remembers everything but learns nothing, neither erring egregiously nor rising above its normal strength,” the IBM scientists wrote in 1990. “Even so, it sometimes produces insights that are overlooked by even top grandmasters.”

Deep Blue was considerably more advanced. At its core, the computer was built to solve complex numerical problems. In front of a chess board, Deep Blue, equipped with data from hundreds of existing master games, would scan the board for features it recognized. Like a human player, the computer thought ahead, exploring potential moves in terms of sequences, envisioning future positions. It numerically rated the moves as it went, finally making the one that came out with the highest rating—the “best” move. Deep Blue was capable of evaluating 100 million positions per second.

Kasparov went into the historic game in 1996 feeling confident, but it soon became clear Deep Blue was a tougher competitor than he’d expected. Kasparov, already known for being an animated player, was visibly frustrated during the game, often shaking his head, says Jeffrey Popyack, a computer science professor at Drexel University who was in the room. At one point, Kasparov spent 27 minutes deliberating before moving his queen. “The thing that really sticks with me now was just the anguish that Kasparov was going through,” Popyack recalls.

Toward the end of game, Kasparov and Deep Blue were like “two sumo wrestlers battling one another at the edge of a high cliff,” as Monty Newborn, chairman of the computer chess committee for the Association of Computing Machines, once put it. Kasparov was mounting an aggressive attack on Deep Blue’s king when the machine made an unusual move—going after a pawn across the board—that suggested the machine was unaware it was in trouble. (“It would be kind of like your house was burning down and you decided to go grocery shopping,” Ashley, the American grandmaster, said.) Turns out the computer had calculated that Kasparov’s move—a bold bluff that would have intimidated a human player—wasn’t going to work. The world champion, visibly distraught, resigned a few moves later.

Modern, game-playing artificial intelligence is, well, even scarier. In 2011, Watson, an IBM super computer capable of answering open-ended questions posed in human language defeated Ken Jennings on Jeopardy! Last month, a computing system developed by Google researchers bested the top human player of Go, a complex 2,500-year-old game that depends heavily on intuition and strategy. (Popyack points out that, despite all that, computers are still not very good at programming other computers.)

Human players are successful if they can spot their opponents’ blind spots, and supercomputers are built to find even the smallest of errors and exploit them. “It’s never going to get tired, and it’s never going to get overconfident, and it’s just going to kill you,” Ashley said. “That’s the difference now. It’s like playing the Terminator.”

Kasparov rebounded in the second game against Deep Blue, and went on to win the whole six-game series. But the scales had been tipped. And in a subsequent matchup in 1997, Deep Blue triumphed. Humans were no longer winning the battle between man and machine.

“It’s a really dangerous business to say, ‘computers will never,’ and then say something after that,” Campbell says.


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10 Big Brain Benefits of Playing Chess

6/7/2014

2 Comments

 
Picture
10 Big Brain Benefits of Playing Chess March 25th, 2012 by Staff Writers
 
Source site:  http://www.onlinecollegecourses.com/2012/03/25/10-big-brain-benefits-of-playing-chess/

Not for nothing is chess known as “the game of kings.” No doubt the rulers of empires and kingdoms saw in the game fitting practice for the strategizing and forecasting they themselves were required to do when dealing with other monarchs and challengers. As we learn more about the brain, some are beginning to push for chess to be reintroduced as a tool in the public’s education. With benefits like these, they have a strong case.



  1. It can raise your IQ Chess has always had an image problem, being seen as a game for brainiacs and people with already high IQs. So there has been a bit of a chicken-and-egg situation: do smart people gravitate towards chess, or does playing chess make them smart? At least one study has shown that moving those knights and rooks around can in fact raise a person’s intelligence quotient. A study of 4,000 Venezuelan students produced significant rises in the IQ scores of both boys and girls after 4 months of chess instruction.

  2. It helps prevent Alzheimer’s Because the brain works like a muscle, it needs exercise like any bicep or quad to be healthy and ward off injury. A recent study featured in The New England Journal of Medicine found that people over 75 who engage in brain-stretching activities like chess are less likely to develop dementia than their non-board-game-playing peers. Just like an un-exercised muscle loses strength, Dr. Robert Freidland, the study’s author, found that unused brain tissue leads to a loss of brain power. So that’s all the more reason to play chess before you turn 75.

  3. It exercises both sides of the brain In a German study, researchers showed chess experts and novices simple geometric shapes and chess positions and measured the subjects’ reactions in identifying them. They expected to find the experts’ left brains being much more active, but they did not expect the right hemisphere of the brain to do so as well. Their reaction times to the simple shapes were the same, but the experts were using both sides of their brains to more quickly respond to the chess position questions.

  4. It increases your creativity Since the right hemisphere of the brain is responsible for creativity, it should come as no surprise that activating the right side of your brain helps develop your creative side. Specifically, chess greatly increases originality. One four-year study had students from grades 7 to 9 play chess, use computers, or do other activities once a week for 32 weeks to see which activity fostered the most growth in creative thinking. The chess group scored higher in all measures of creativity, with originality being their biggest area of gain.

  5. It improves your memory Chess players know — as an anecdote — that playing chess improves your memory. Being a good player means remembering how your opponent has operated in the past and recalling moves that have helped you win before. But there’s hard evidence also. In a two-year study in 1985, young students who were given regular opportunities to play chess improved their grades in all subjects, and their teachers noticed better memory and better organizational skills in the kids. A similar study of Pennsylvania sixth-graders found similar results. Students who had never before played chess improved their memories and verbal skills after playing.

  1. It increases problem-solving skills A chess match is like one big puzzle that needs solving, and solving on the fly, because your opponent is constantly changing the parameters. Nearly 450 fifth-grade students were split into three groups in a 1992 study in New Brunswick. Group A was the control group and went through the traditional math curriculum. Group B supplemented the math with chess instruction after first grade, and Group C began the chess in first grade. On a standardized test, Group C’s grades went up to 81.2% from 62% and outpaced Group A by 21.46%.

  2. It improves reading skills In an oft-cited 1991 study, Dr. Stuart Margulies studied the reading performance of 53 elementary school students who participated in a chess program and evaluated them compared to non-chess-playing students in the district and around the country. He found definitive results that playing chess caused increased performance in reading. In a district where the average students tested below the national average, kids from the district who played the game tested above it.

  3. It improves concentration Chess masters might come off like scattered nutty professors, but the truth is their antics during games are usually the result of intense concentration that the game demands and improves in its players. Looking away or thinking about something else for even a moment can result in the loss of a match, as an opponent is not required to tell you how he moved if you didn’t pay attention. Numerous studies of students in the U.S., Russia, China, and elsewhere have proven time and again that young people’s ability to focus is sharpened with chess.

  4. It grows dendrites Dendrites are the tree-like branches that conduct signals from other neural cells into the neurons they are attached to. Think of them like antennas picking up signals from other brain cells. The more antennas you have and the bigger they are, the more signals you’ll pick up. Learning a new skill like chess-playing causes dendrites to grow. But that growth doesn’t stop once you’ve learned the game; interaction with people in challenging activities also fuels dendrite growth, and chess is a perfect example.

  5. It teaches planning and foresight Having teenagers play chess might just save their lives. It goes like this: one of the last parts of the brain to develop is the prefrontal cortex, the area of the brain responsible for planning, judgment, and self-control. So adolescents are scientifically immature until this part develops. Strategy games like chess can promote prefrontal cortex development and help them make better decisions in all areas of life, perhaps keeping them from making a stupid, risky choice of the kind associated with being a teenager.


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