UPDATE Mar 12th 2016: AlphaGo has won the third game against Lee Sedol, and has thus won the five-game match. That was the score, as The Economist went to press, in the latest round of the battle between artificial intelligence (AI) and the naturally evolved sort. The field of honour is a Go board in Seoul, South Korea--a country that cedes to no one, least of all its neighbour Japan, the title of most Go-crazy place on the planet. To the chagrin of many Japanese, who think of Go as theirs in the same way that the English think of cricket, the game's best player is generally reckoned to be Lee Sedol, a South Korean. Mr Lee is in the middle of a five-game series with AlphaGo, a computer program written by researchers at DeepMind, an AI software house in London that was bought by Google in 2014.

Four Cool Ways to Use Neural Networks in Games

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In our book, AI for Game Developers, we cover many different AI techniques that are used in games. Many of the techniques we cover, such as chasing and evading, pathfinding, finite state machines, and rules-based systems, among others, have obvious applications in games. However, some of the other techniques we cover, such as neural networks, genetic algorithms, and Bayesian techniques, are not as familiar and thus their applications in games may not be as obvious. Nonetheless, these latter techniques offer compelling capabilities when applied in games and they are quickly gaining popularity, as evidenced by their appearances in game development literature, conferences, and indeed the games. Throughout our book we give you multiple code examples and additional ideas of how you can apply all of the techniques we cover in your own games.

Online chess game lets you see what the computer is thinking


Artificial intelligence has shown what it can do when facing off against humans in ancient board games, with Deep Blue and Alpha Go already proving their worth on the world stage. While computers playing chess is nothing new, an online version of the ancient game lifts the veil of AI to let players see what the AI is thinking. You make your move and then see the computer come to life, calculating thousands of possible counter moves. Thinking Machine 6 is an AI-based concept art piece created by Martin Wattenberg. Rather than making players into chess champions, it shows the AI thinking process.

Smartphone AI Won't Save Your Life in a Crisis Chop Dawg


You are reading a guest blog post by John Boitnott. Artificial Intelligence is not by any means a new concept. It's been the stuff of science fiction speculation for years, and has been a repeated point of debate in popular culture for quite some time. Humanity's relationship to AI really came to the forefront of contemporary technological debate when IBM's Deep Blue computer defeated world chess champion Garry Kasparov in 1996. The trend of man vs. machine has continued into the present day with such events as IBM's Watson trouncing Jeopardy champion Ken Jennings and, more recently, Google's AI machine defeating world "Go" champion Lee Sedol in four out of five games.

How an artificial intelligence learnt to play


Go looks simple, deceptively so. The Chinese board game is played on a board with a grid of 19x19 lines. The object is for two players to alternately place black and white markers on vacant intersections of those lines. And now, this nearly 3,000-year-old board game is a frontier of Artificial Intelligence development. At the time of writing, Google's DeepMind AI's AlphaGo program has played four games of a five game series against Go world champion, South Korea's Lee se-Dol.