AlphaGo is going out on top. After beating Ke Jie, the world’s best player of the ancient Chinese board game Go, for the third time today at the Future of Go Summit in Wuzhen, Google’s DeepMind unit announced that it would be the last event match the AI plays. In a statement, DeepMind co-founder and co-CEO Demis Hassabis said the reason was that this week’s summit represented “the highest possible pinnacle for AlphaGo as a competitive program.”

AlphaGo rose to prominence a little over a year ago when it unexpectedly defeated legendary player Lee Se-dol 4-1 in a match held in Seoul. Most computer scientists expected the feat of beating a top Go player with artificial intelligence to be decades away due to the game’s complexity and nuance, but with this week’s comprehensive defeat of Ke Jie the matter has been settled.

“We can’t wait to see what comes next.”

“The research team behind AlphaGo will now throw their considerable energy into the next set of grand challenges, developing advanced general algorithms that could one day help scientists as they tackle some of our most complex problems, such as finding new cures for diseases, dramatically reducing energy consumption, or inventing revolutionary new materials,” Hassabis says. “If AI systems prove they are able to unearth significant new knowledge and strategies in these domains too, the breakthroughs could be truly remarkable. We can’t wait to see what comes next.”

AlphaGo’s success has brought profound change to the world of Go, most obviously seen this week in the way Ke Jie used previously unorthodox moves that the AI had employed itself and forced human players to reevaluate. And although AlphaGo has played its last competitive match, DeepMind will release the data from 50 games of the AI playing against itself for the Go community to study. DeepMind is also working on a teaching tool based on AlphaGo to be released sometime in the future. Ke Jie will collaborate with DeepMind on the tool, which Hassabis says should give “all players and fans the opportunity to see the game through the lens of AlphaGo.”

“We have always believed in the potential for AI to help society discover new knowledge and benefit from it, and AlphaGo has given us an early glimpse that this may indeed be possible,” Hassabis says. “More than a competitor, AlphaGo has been a tool to inspire Go players to try new strategies and uncover new ideas in this 3,000 year-old game.”

DeepMind doesn’t plan to give AlphaGo itself a wide release, however. Hassabis told The Verge earlier this week that while there were “complications” in doing so, he’s more than happy for others to make use of DeepMind’s research themselves. Programs like Tencent’s Fine Art and Japan’s DeepZenGo have used similar deep-learning techniques to achieve around 9th-dan level, according to Hassabis, which is the highest ranking a human can attain and represents a far stronger degree of play than the previous state of the art. DeepMind will soon publish another paper on how it architected the latest version of AlphaGo, AlphaGo Master, and Hassabis expects other companies to learn from the new research.

AlphaGo has quite literally been a game-changer; now it’s up to humans to see how they can make use of it, and DeepMind to find out where it can go from here.