DeepMind announced that AlphaGo will no longer compete: “This week’s series of thrilling games with the world’s best players … has been the highest possible pinnacle for AlphaGo as a competitive program. For that reason, the Future of Go Summit is our final match event with AlphaGo.”
This reason is rubbish. Could AlphaGo repeat its string of 60 victories in no-komi games? Could it win a match giving handicap stones? If AlphaGo wanted to keep competing, there are many more challenges left for it to conquer.
DeepMind used Go as a very successful testbed for its deep learning algorithms: a testbed that has measurable outcomes and can generate its own test data. Winning against the world’s best doesn’t make that testbed obsolete. DeepMind said that this year’s version was using ten times less computing power than last year’s AlphaGo. Could they improve the algorithms by another factor of ten? Hundred? Thousand? Yes, by all means push into other domains and apply what you’ve learned, but don’t abandon the testbed. You have ideas on how to improve your learning algorithm for medical diagnosis or self-driving cars? Testing the effectiveness of those improvements will be a lot harder than in Go.
I’m glad the DeepMind team is publishing a set of 50 AlphaGo self-play games, and that they’re working on a teaching tool. But not pushing AlphaGo forward competitively is a mistake.