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Landmark from Google as AI beats a human

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A system developed by Google has mastered the ancient Chinese game of Go, a progression being hailed as a significant development in the field of artificial intelligence (AI).

Go is a game based around the placement of black or white stones on a board. Competitors try to capture their opponents stones or secure empty space.

While it may seem simple, the game is incredibly complex: there are said to be more possible positions than there are atoms in the universe, with Go seen as a more intuitive game than chess, and thus harder for computers to master.

A team from Google DeepMind developed a program called AlphaGo to try and "crack" the Game. Based in London, Google DeepMind was acquired by Google in 2014.

On Wednesday it was announced that AlphaGo had beaten Fan Hui – the best player in Europe – five nil in a closed doors match last October.

"It was the first time a computer program has ever beaten a professional Go player," Demis Hassabis, CEO of Google DeepMind, said in a blog post.

The findings are published in the journal Nature. In March AlphaGo will play the world's best Go player, Lee Sedol, in Seoul.


The potential of the research is significant.

"While games are the perfect platform for developing and testing AI algorithms quickly and efficiently, ultimately we want to apply these techniques to important real-world problems," Hassabis added.

"Because the methods we've used are general-purpose, our hope is that one day they could be extended to help us address some of society's toughest and most pressing problems, from climate modelling to complex disease analysis," Hassabis added.

As well as mastering ancient board games, Google is also looking to transform the way our phones operate. On Wednesday Movidius announced that it was working with Google to "accelerate the adoption of deep learning within mobile devices."

According to the chip maker, the collaboration will see Google deploy its "advanced neural computation engine on Movidius' low-power platform."

This, Movidius said, will enable future devices to possess the capability to comprehend audio and images with "incredible speed and accuracy, offering a more personal and contextualized computing experience."