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Researchers built an AI that plays chess like a person, not a super computer

Engadget

We mere mortals haven't truly been competitive against artificial intelligence in chess in a long time. It's been 15 years since a human has conquered a computer in a chess tournament. However, a team of researchers have developed an AI chess engine that doesn't set out to crush us puny humans -- it tries to play like us. The Maia engine doesn't necessarily play the best available move. Instead, it tries to replicate what a human would do.


Artificial intelligence and machine learning: A new blueprint for the fintech industry

#artificialintelligence

The term Artificial Intelligence was coined 70 years ago as the stuff of fantasy fiction and about 50 years post that nothing much moved. Then, in 1997 like a bolt from the blue, IBM's Deep Blue defeated world chess champion Garry Kasparov 4-2 in a six game series. Since then, machines have beaten humans at far more complex games – Go, Poker, Dota 2. Computing power grew over a trillion times in the last 50 years. Can you name any industry/trend that has evolved by this order of magnitude? The computer that helped navigate Apollo 11's moon landing had the power of two Nintendo consoles. You have a lot more power in your smartphone today.


Artificial intelligence and machine learning: A new blueprint for the fintech industry

#artificialintelligence

The term Artificial Intelligence was coined 70 years ago as the stuff of fantasy fiction and about 50 years post that nothing much moved. Then, in 1997 like a bolt from the blue, IBM's Deep Blue defeated world chess champion Garry Kasparov 4-2 in a six game series. Since then, machines have beaten humans at far more complex games – Go, Poker, Dota 2. Computing power grew over a trillion times in the last 50 years. Can you name any industry/trend that has evolved by this order of magnitude? The computer that helped navigate Apollo 11's moon landing had the power of two Nintendo consoles. You have a lot more power in your smartphone today.


Are Computers That Win at Chess Smarter Than Geniuses?

#artificialintelligence

But then there was the Chinese game of go (pictured), estimated to be 4000 years old, which offers more "degrees of freedom" (possible moves, strategy, and rules) than chess (2 10170). As futurist George Gilder tells us, in Gaming AI, it was a rite of passage for aspiring intellects in Asia: "Go began as a rigorous rite of passage for Chinese gentlemen and diplomats, testing their intellectual skills and strategic prowess. Later, crossing the Sea of Japan, Go enthralled the Shogunate, which brought it into the Japanese Imperial Court and made it a national cult." Then AlphaGo, from Google's DeepMind, appeared on the scene in 2016: As the Chinese American titan Kai-Fu Lee explains in his bestseller AI Super-powers,8 the riveting encounter between man and machine across the Go board had a powerful effect on Asian youth. Though mostly unnoticed in the United States, AlphaGo's 2016 defeat of Lee Sedol was avidly watched by 280 million Chinese, and Sedol's loss was a shattering experience. The Chinese saw DeepMind as an alien system defeating an Asian man in the epitome of an Asian game.


If a robot is conscious, is it OK to turn it off? The moral implications of building true AIs

#artificialintelligence

In the "Star Trek: The Next Generation" episode "The Measure of a Man," Data, an android crew member of the Enterprise, is to be dismantled for research purposes unless Captain Picard can argue that Data deserves the same rights as a human being. Naturally the question arises: What is the basis upon which something has rights? What gives an entity moral standing? The philosopher Peter Singer argues that creatures that can feel pain or suffer have a claim to moral standing. He argues that nonhuman animals have moral standing, since they can feel pain and suffer.


Pitting Computers Against Each Other . . . in Chess

Communications of the ACM

For those of us involved in programming computers to play chess, it has been a great adventure. ACM annual tournaments began in 1970 (50 years ago!) and were hosted year after year for a quarter-century by the organization. They were terrific catalysts for progress in the field, and deserve major credit for the eventual 1997 defeat of then-World Champion Garry Kasparov. I feel human intelligence has been vastly overrated. We humans haven't learned how not to fight wars over various explanations of how the universe or man came into being.


If a Robot Is Conscious, Is It OK to Turn It Off? The Moral Implications of Building True AIs

#artificialintelligence

In the Star Trek: The Next Generation episode "The Measure of a Man," Data, an android crew member of the Enterprise, is to be dismantled for research purposes unless Captain Picard can argue that Data deserves the same rights as a human being. Naturally the question arises: What is the basis upon which something has rights? What gives an entity moral standing? The philosopher Peter Singer argues that creatures that can feel pain or suffer have a claim to moral standing. He argues that nonhuman animals have moral standing, since they can feel pain and suffer.


"Just A Few Techie Definitions"

#artificialintelligence

This data/information is entered into one of my published books, “A Few Tech Definitions From A to Z…” I thought I might help as many as I can to understand what all those “techie speak” words, abbreviations, and symbols imply. To the student(s) who


How AI Has Already Revolutionised the Online Gaming Industry

#artificialintelligence

Artificial Intelligence already influences many parts of modern life. Simple formulas and complex AI systems work away without us even knowing. That is already the case in video gaming and has been for decades. Game developers have used artificial intelligence in numerous ways since the advent of this technology. Pathfinding is used to find a way from Point A and Point B like the ghosts in Pac-Man. Finite State Machines transform those same ghosts from chasers to fleers in-game.


Chess2vec: Learning Vector Representations for Chess

arXiv.org Artificial Intelligence

We conduct the first study of its kind to generate and evaluate vector representations for chess pieces. In particular, we uncover the latent structure of chess pieces and moves, as well as predict chess moves from chess positions. We share preliminary results which anticipate our ongoing work on a neural network architecture that learns these embeddings directly from supervised feedback. The fundamental challenge for machine learning based chess programs is to learn the mapping between chess positions and optimal moves [5, 3, 7]. A chess position is a description of where pieces are located on the chessboard. In learning, chess positions are typically represented as bitboard representations [1]. A bitboard is a 8 8 binary matrix, same dimensions as the chessboard, and each bitboard is associated with a particular piece type (e.g.