Chess


Blue state GOP gov digs in as Dems vow takedown - Kamala Harris spends big with media firm that boosted Bernie Sanders' national profile

FOX News

"The latest polling that we have shows about 6 percent of the people in Maryland strongly disapprove of the job I'm doing," Hogan told Fox News, during a recent event in voter-rich Montgomery County. Roughly half the state's 3.9 million voters are registered Democrats; Republicans haven't controlled the General Assembly since the early 1900s; the last GOP senator was elected to Congress in 1970; and a Democrat has been governor in roughly 42 of the past 49 years. "If Democrats are raring to steal one back from Trump, then Maryland is ripe for the picking," said Maryland Republican Party official Rob Carter, who suggested recent polling data shows Democrats in the state are "as strong as ever, even a little bit stronger." "But you have to show up and have a message that appeals to voters," said Edwards, elected to four terms with an average 79 percent of the general election vote before losing a 2016 Senate bid.


The Bots Beat Us. Now What?

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He hadn't played a recorded game of chess for five years, since defeating Boris Spassky and the Soviet machine in the match of the century in Reykjavik, Iceland, capturing the world championship and becoming an American Cold War hero. Bobby Fischer, the troubled American chess hero, embarrassed a chess-playing computer in 1977. We lost our collective opposable-thumb grip on chess roughly 20 years earlier, when our human representative Garry Kasparov, a world chess champion, fell in a six-game match at the hands of IBM's supercomputer called Deep Blue. Campbell, a former student of Berliner's, still works on artificial intelligence at IBM, where he has won the company chess championship the past two years.


A Brutal Intelligence: AI, Chess, and the Human Mind - Los Angeles Review of Books

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Fascination with digital computers intensified during the 1950s, and the so-called "thinking machines" began to influence theories about the human mind. It took only a few decades after Shannon wrote his paper for engineers to build a computer that could play chess brilliantly. Even though it was the first time a machine had beaten a world champion in a formal match, to computer scientists and chess masters alike the outcome wasn't much of a surprise. Whereas most software programs apply rules to data, machine-learning algorithms do the reverse: they distill rules from data, and then apply those rules to make judgments about new situations.


Garry Kasparov: "Deep Thinking" Talks at Google

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Garry Kasparov and DeepMind's CEO Demis Hassabis discuss Garry's new book "Deep Thinking", his match with Deep Blue and his thoughts on the future of AI in the world of chess. Chess has long been the fulcrum in development of machine intelligence; the hoax automaton'The Turk' in the 18th century and Alan Turing's first chess program in 1952 were two early examples of the quest for machines to think like humans -- a talent we measured by their ability to beat their creators at chess. During the twenty years since playing Deep Blue, he's played both with and against machines, learning a great deal about our vital relationship with our most remarkable creations. In this breakthrough book, Kasparov tells his side of the story of Deep Blue for the first time -- what it was like to strategize against an implacable, untiring opponent -- the mistakes he made and the reasons the odds were against him.


Garry Kasparov on intelligent machines - The Manufacturer

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In 1997, the world chess champion Garry Kasparov went into battle with a chess-playing computer, Deep Blue, and lost. It's not hard to understand why opponents found Garry Kasparov so formidable. Garry Kasparov was at Hay to discuss his new book Deep Thinking, the product of two decades' research into artificial intelligence (AI), machine learning and our relationship with both. Of course, Google has just taken the issue into new territory with AlphaGo, that beat the world champion Go player by combining brute force computing with machine learning and deep neural networks.


Why are AI predictions so terrible?

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In 1997, IBM's Deep Blue beat world chess champion Gary Kasparov, the first time an AI technology was able to outperform a world expert in a highly complicated endeavor. Another contributing factor to bad AI predictions is human bias. In fact, the researchers' bad predictions make more sense through this lens. Take this example often used on logic tests: If the number of lily pads on a lake doubles every day, and the lake will be full at 30 days, how many days will it take for the lake to be half full?


20 Years after Deep Blue: How AI Has Advanced Since Conquering Chess

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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. 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. I was part of a group of graduate students at Carnegie Mellon University that IBM approached. IBM noticed the successes that we were having building this machine on a shoestring budget and thought it would be interesting to have a group of us join IBM Research [in late 1989] to develop the next generation of this machine, called Deep Blue.


20 Years after Deep Blue: How AI Has Advanced Since Conquering Chess

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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. 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. I was part of a group of graduate students at Carnegie Mellon University that IBM approached. IBM noticed the successes that we were having building this machine on a shoestring budget and thought it would be interesting to have a group of us join IBM Research [in late 1989] to develop the next generation of this machine, called Deep Blue.


Centaur Chess Shows Power of Teaming Human and Machine

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The story of IBM's Deep Blue computer defeating world chess champion Garry Kasparov in 1997 has been told so many times that it's practically shorthand for the philosophical debate over man vs. machine. Teaming the two in chess, experts say, produces a force that plays better chess than either humans or computers can manage on their own. The Freestyle games are timed, forcing players to think on their feet while managing the clock. "If you merge millions of games played by computers with high-caliber human games, you get something that is quantitatively and qualitatively superior to any commercial product," says Nelson Hernandez, a suburban Washington D.C. data analyst who is a member of one of the most successful Freestyle teams in history.


One of the greatest chess players of all time, Garry Kasparov, talks about artificial intelligence and the interplay between machine learning and humans

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Because when you look back at my matches that I've played with chess computers, now, if we stick with the intelligence as a result, then by the definition of its output, Deep Blue was intelligent because it played grand-master-level chess. A free chess app on your mobile is better than Deep Blue, stronger than Deep Blue. Looking, for instance, at the games we played in 1997, and using modern computers, I found out that it's not just I who made mistakes, but Deep Blue made quite a few serious mistakes ... serious mistakes that could bring the game from a drawing position to a losing one. Holodny: It's easy to see how human's intuition can be weaker than a computer, but do you think there are examples when it's an advantage to act on intuition?