Have we hit a major artificial intelligence milestone?

Image: REUTERS/China DailyStudents play the board game "Go", known as "Weiqi" in Chinese, during a competition.

Google’s computer program AlphaGo has defeated a top-ranked Go player in the first round of five historic matches – marking a significant achievement in the development of artificial intelligence.

AlphaGo’s victory over a human champion shows an artificial intelligence system has mastered the most complex game ever designed. The ancient Chinese board game is vastly more complicated than chess and is said to have more possible configurations than there are atoms in the Universe.

The battle between AlphaGo, developed by Google’s Deepmind unit, and South Korea’s Lee Se-dol was said by commentators to be close, with both sides making some mistakes.

Game playing is an important way to measure AI advances, demonstrating that machines can outperform humans at intellectual tasks.

AlphaGo’s win follows in the footsteps of the legendary 1997 victory of IBM supercomputer Deep Blue over world chess champion Garry Kasparov. But Go, which relies heavily on players’ intuition to choose among vast numbers of board positions, is far more challenging for artificial intelligence than chess.

Speaking in the lead-up to the first match, Se-dol, who is currently ranked second in the world behind fellow South Korean Lee Chang-ho, said: “Having learned today how its algorithms narrow down possible choices, I have a feeling that AlphaGo can imitate human intuition to a certain degree.”

Demis Hassabis, founder and CEO of DeepMind, which was acquired by Google in 2014, previously described “Go as the pinnacle of game AI research” and the “holy grail” of AI since Deep Blue beat Kasparov.

Experts had predicted it would take another decade for AI systems to beat professional Go players. But in January, the journal Nature reported that AlphaGo won a five-game match against European champion Fan Hui. Since then the computer program’s performance has steadily improved.

Mastering the game of Go. Nature

While DeepMind’s team built AlphaGo to learn in a more human-like way, it still needs much more practice than a human expert, millions of games rather than thousands.

Potential future uses of AI programs like AlphaGo could include improving smartphone assistants such as Apple’s Siri, medical diagnostics, and possibly even working with human scientists in research.

ORIGINAL: World Economic Forum

by Rosamond Hutt, Senior Producer, Formative Content

9 March 2016