Google's AlphaGo scores 4-1 against South Korean Go player

AlphaGo won a seesaw game that even saw it making a bad mistake

Google DeepMind’s AlphaGo artificial-intelligence program won the last round in a five-game contest against top Go player Lee Se-dol, despite making a bad mistake during play.

The 4-1 margin for AlphaGo in the games played in Seoul, South Korea was not as large as the 5-0 win by the program against an European Go player in October, but carries more impact because of Lee's standing in the Go game.

For the most part of the game, commentators were not sure AlphaGo would win. Google DeepMind CEO Demis Hassabis said in a tweet, for example, that AlphaGo made a bad mistake early in the game, but was trying "hard to claw it back."

The AlphaGo program has been described as the next frontier in AI because of its ability to to learn from its experience, which according to some experts explained its unexpected and far-from-human moves that were nevertheless successful.

The wins by AlphaGo are a momentous milestone in the field of AI since IBM’s Deep Blue defeated Garry Kasparov in chess in 1997, said Howard Yu, professor of strategic management and innovation at IMD business school, about the three consecutive wins by the program.

The Go game has been described as a more complex strategy game than even chess. Players take turns to place black or white pieces, called “stones,” on the 19-by-19 line grid, to aim to capture the opponent's stones by surrounding them and encircling more empty space as territory.

AlphaGo's loss on Sunday to Lee, however, highlighted that artificial neural networks - the hardware and software equivalent of the human central nervous system - can act strangely because of hard-to-find “blind spots.” It is possible that a strong player can force AlphaGo into a situation that exposes its hidden blind spots, said David Silver, a key researcher on the AlphaGo project.

Much of the discussion ahead of the final game on Tuesday was on a move made by Lee in the fourth game on Sunday, which appeared to degrade the AI program’s performance subsequently. After taking a quick look at the logs, Hassabis said AlphaGo had given a probability of less than 1 in 10,000 for Lee's move, so it found the move very surprising.

“This meant that all the prior searching #AlphaGo had done was rendered useless, and for a while it misevaluated the highly complex position,” Hassabis said in a tweet on Tuesday. He added that the neural networks were trained through self-play “so there will be gaps in their knowledge, which is why we are here: to test AlphaGo the limit.”

The highly-publicized contest has established Google DeepMind’s credentials at the frontier of AI. Besides using the technology internally, Google is expected to offer the technology for a variety of applications including healthcare and scientific applications to start with.

The AI system is still a prototype, said Hassabis, so Google DeepMind is still going to be doing a lot of testing and training of the platform, including presumably having a go at removing the hidden blind spots, before releasing the technology for mission-critical applications.

Join the newsletter!

Or
Error: Please check your email address.
Rocket to Success - Your 10 Tips for Smarter ERP System Selection

Tags Googlealphago

Keep up with the latest tech news, reviews and previews by subscribing to the Good Gear Guide newsletter.

John Ribeiro

IDG News Service
Show Comments

Essentials

James Cook University - Master of Data Science Online Course

Learn more >

Mobile

Victorinox Werks Professional Executive 17 Laptop Case

Learn more >

Sansai 6-Outlet Power Board + 4-Port USB Charging Station

Learn more >

Exec

Budget

Back To Business Guide

Click for more ›

Brand Post

Bitdefender 2018

Roam freely in the digital world. Critically acclaimed performance and security at your fingertips.

Most Popular Reviews

Latest Articles

Resources

PCW Evaluation Team

Louise Coady

Brother MFC-L9570CDW Multifunction Printer

The printer was convenient, produced clear and vibrant images and was very easy to use

Edwina Hargreaves

WD My Cloud Home

I would recommend this device for families and small businesses who want one safe place to store all their important digital content and a way to easily share it with friends, family, business partners, or customers.

Walid Mikhael

Brother QL-820NWB Professional Label Printer

It’s easy to set up, it’s compact and quiet when printing and to top if off, the print quality is excellent. This is hands down the best printer I’ve used for printing labels.

Ben Ramsden

Sharp PN-40TC1 Huddle Board

Brainstorming, innovation, problem solving, and negotiation have all become much more productive and valuable if people can easily collaborate in real time with minimal friction.

Sarah Ieroianni

Brother QL-820NWB Professional Label Printer

The print quality also does not disappoint, it’s clear, bold, doesn’t smudge and the text is perfectly sized.

Ratchada Dunn

Sharp PN-40TC1 Huddle Board

The Huddle Board’s built in program; Sharp Touch Viewing software allows us to easily manipulate and edit our documents (jpegs and PDFs) all at the same time on the dashboard.

Featured Content

Product Launch Showcase

Latest Jobs

Don’t have an account? Sign up here

Don't have an account? Sign up now

Forgot password?