Computer beats human in ancient Chinese game of Go

But people have been wrestling with it for millennia – and the game has confounded some of the most advanced artificial intelligence around.

The game, which is played by 40 million people around the world, involves people taking turns to place black or white stones on a board in a bid to capture an opponent’s stones and territory. The object is merely to avoid having your stones hemmed in on four sides by your opponent’s stones.

While computers learned to outclass humans at checkers and chess in the ’90s, Go – a 2,500-year old game – was still vexing computer scientists. The game is much tougher than chess for computers because of the number of ways a match can play out.

A computer has bested humanity at one of the most complex strategy games ever devised. That means it’s impossible to play the game by brute force – trying all possible sequences of moves until you find a winning strategy. But researchers at Google DeepMind say their software, known as AlphaGo, takes a different approach. The program got smarter by learning about games played by human experts while also playing thousands of games between its neural networks, allowing it to better master Go.

The first, “policy network” narrows the search at each turn to only those moves most likely to lead to a win.

“You can think of him as the Roger Federer of the Go world”, Hassabis said. But playing against a human expert is a much greater challenge than playing other computers because, well, the pros are still so much better-they have years of experience with the game, and a kind of intuition about how to play it. So when AlphaGo won the game 5-0, it was a big deal.

The program can beat existing go software 99.8% of the time, and it won all five games against reigning European champion Fan Hui in October.

“We will spend more of our lives interacting with (computers), and it will be important for them to understand our emotional states”, says Walsh.

On Wednesday, DeepMind, the taciturn artificial intelligence arm of the search engine, made a big announcement: Its program has defeated a champion human Go player.

In March, the program will put its skills to the ultimate test in a match against Lee Sedol, now considered the best Go player in the world. There are more configurations of the board than there are atoms in the Universe. The standard AI approach to playing games is based on deep search to evaluate positions.

The same techniques used to teach AlphaGo to play Go could be used to develop digital assistants that will automate parts of our daily lives, diagnose medical conditions faster than human doctors and help solve major scientific challenges such as modelling climate change and curing diseases, Mr Hassabis said.

In what may be the AI world’s equivalent of trash talking, Silver said there was “zero chance” that AlphaGo could be beaten by IBM’s Watson computer, which is optimized to handle a wide array of knowledge, but at a shallower depth.

Go originated in China and has a long heritage. Beating a champion at Go has always been considered a “grand challenge” in AI research, for the game is far harder for computers than chess. Not to be outdone, Facebook announced earlier this morning that they are close to creating an artificial intelligence program that can beat a human player.

“This has been the holy grail since Deep Blue beat Kasparov at chess, and it’s held out for over 20 years”.

“It was one of the most exciting moments in my career”, Chouard said at a press briefing January 25. This approach has produced several artificial-intelligence breakthroughs in recent years, including computers that can identify objects in images more consistently than humans can.

But there are some things the researchers won’t do with AI. In an article in Nature, the artificial intelligence researchers at DeepMind explain how they developed the system. He also pointed out that he’s one of the signers of an open letter calling for a ban on autonomous weapons. In a paper published today in Nature, DeepMind researchers revealed how the system was constructed and how it was able to succeed where decades of previous Go systems have failed. We take it for granted that Amazon has a pretty good idea of what we might want to buy, for instance, or that Google can complete our partially typed search term, though these are both due to recent advances in AI.