Microsoft’s Mahjong-winning AI could lead to sophisticated finance market prediction systems

Last August, Microsoft Research Asia detailed an AI system dubbed Super Phoenix (Suphx for short) that could defeat Mahjong players after learning from only 5,000 matches. A revised preprint paper out this week delves a bit deeper, revealing that Suphx — whose performance improved with additional training — is now rated above 99.99% of all ranked human players on Tenhou, a Japan-based global online Mahjong competition platform with over 350,000 members.

Building superhuman programs for games is a longstanding goal of the AI research community — and not without good reason. Games are an analog of the real world, with a measurable objective, and they can be played an infinite amount of times across hundreds (or thousands) of powerful machines. Moreover, its researchers assert that the learnings are applicable to other domains, like the enterprise, where mundane but cognitively demanding tasks impact workers’ productivity.