After Win in China, AlphaGo’s Designers Explore New AI

WUZHEN, CHINA — After winning its three-game match against Chinese grandmaster Ke Jie, the world’s top Go player, AlphaGo is retiring.

Demis Hassabis, the CEO and founder of DeepMind, the Google artificial intelligence lab that built this historic machine, tells WIRED he will now move the machine’s designers to other projects. “This is some of the top people in the company,” Hassabis says. “The idea is to really explore what we can do in other domains.” Considering the world-shaking success of AlphaGo, that is a very powerful idea.

Last March, in Seoul, South Korea, AlphaGo became the first machine to beat a top player at the ancient game of Go when it defeated Korean grandmaster Lee Sedol—something that didn’t seem possible just a few years before—and in the year since, Hassabis and team significantly improved the machine. Today, in Wuzhen, China, AlphaGo won its third game against Ke Jie, and much like the other two, the game held little drama. But at the same time, the machine sent the usual ripples across the worldwide Go community.

When DeepMind first unveiled AlphaGo, serious students of the game questioned whether it was skillful enough to challenge the world’s best players. And when it topped Lee Sedol, many lamented that a machine had eclipsed the powers of humanity, somehow mimicking the intuition required to play this enormously complex game. But as the DeepMind team continued to improve this surprisingly powerful machine, the top Go players couldn’t get enough of it. They’ve repeatedly called on DeepMind to release the countless games that AlphaGo has played behind closed doors, seeing the machine’s play as a window into the future of Go.

“AlphaGo extends the horizon of Go games,” Chinese grandmaster Lian Xiao said this week after playing a match alongside the machine. “It brings more imagination.”

So, as AlphaGo completes its 18-month arc, DeepMind is giving Go players at least some of what they want. Today, during the press conference following the game, Hasssabis and DeepMind announced they will publicly release 50 games AlphaGo played against itself inside the vast data centers that underpin Google’s online empire. “Some of the great games in history may be played on these servers,” Hassabis says.

Quite literally, AlphaGo learns to master the mysteries of Go by playing game after game against itself, and though it typically does this is under strict time limits—seconds or milliseconds for each move—DeepMind has released games that played out over several hours, much like professional matches. “These are beautiful games, with moves no one has seen,” says Fan Hui, the European Go champion who helped train AlphaGo.

But as the announcement was made, some Go players complained that those 50 games were a mere pittance—considering that the machine has played hundreds of thousands of games against itself over the past several months, if not millions. They believe there is so much more to learn from the machine they once viewed with so much skepticism and fear.

The evolution of AlphaGo is just one demonstration of the way artificial intelligence can not just replace human skills but somehow advance them. So many of the top players have changed their play after watching AlphaGo, particularly since a new version of the machine won 60 online matches during a pseudonym in January. This week in Wuzhen, Je Kie opened the first game with the rather unusual strategy, “3-3 point,” that AlphaGo used time and again during those 60 matches.

Hassabis and other researchers believe that AI will soon have a similar effect in the world of healthcare and scientific research, pushing humans to places they couldn’t travel on their own. And that’s no idle prediction. Underpinned by technologies that are already reinventing the world’s most popular internet services—even as they rapidly push into driverless cars and robotics—AlphaGo is very much a proxy for the near future of AI as a whole.

According to Hassabis and lead researcher David Silver, the new incarnation of the machine is something the DeepMind team can apply to so many tasks beyond the game of Go. So, after the match in China, DeepMind is disbanding the team that worked on Go. Researchers like Silver and Thore Graepel will spend their time working on the rest of AI’s future.



Wired