British Go Journal 174, including the full report on the AlphaGo v Fan Hui match is now available online to members at http://www.britgo.org/bgj/bgj174
We're still getting additional media coverage of this match - see http://www.britgo.org/history/media for the latest.
The ancient Chinese game of Go is one of the last games where the best human players can still beat the best artificial intelligence players. Last year, the Facebook AI Research team started creating an AI that can learn to play Go.
Scientists have been trying to teach computers to win at Go for 20 years. We're getting close, and in the past six months we've built an AI that can make moves in as fast as 0.1 seconds and still be as good as previous systems that took years to build. Our AI combines a search-based approach that models every possible move as the game progresses along with a pattern matching system built by our computer vision team.
The researcher who works on this, Yuandong Tian, sits about 20 feet from my desk. I love having our AI team right near me so I can learn from what they're working on.
You can learn more about this research here: http://arxiv.org/abs/1511.06410
[He also posted a video: https://www.facebook.com/zuck/videos/10102619979032811/]
We've issued the following Press Release today (27th January 2016):
A computer program developed by Google DeepMind (AlphaGo) to play the Oriental game of Go has beaten the three-times European Go Champion and Chinese professional Fan Hui (shown on the right in the photo, courtesy of Google DeepMind). This is the first time that a Go-professional has lost such a match, and not only that, by a clean sweep in all 5 games. This signifies a major step forward in one of the great challenges in the development of artificial intelligence - that of game-playing.
These findings were reported in a peer-reviewed study published in the scientific journal Nature: Silver D. et al. Mastering the game of Go with deep neural networks and tree search.
Also winning three games were Roger Huyshe (3k Shropshire), Malcolm Hagan (5k Winchester), Stephen Bailey (7k Arundel) and Robert Scantlebury (9k Sheffield). Paul Barnard (2k Swindon) won 2.5. All players on two wins won a prize each too, with Hitachi maintaining their generous Go-support with a fine array of prizes.
Best teams were Arundel (Steve, Malcolm, Pauline and Casey) on 9/12 and "No Go" (Roella, Edmund, Charlotte and Zaki) on 8/12. The 13x13 prizes went to Edmund Smith (8k Milton School) with 3/4 and Lily Danson (15k Cheadle Hulme School) with 4/7.
The UK Youth GO team have finished a respectable sixth out of the twelve teams competing in the European online Youth Go Team Tournament. This year the draw was an accelerated Swiss which meant the top teams were paired against each other from an early stage. This gave our team more chances to play more evenly matched opponents. We picked up wins against Poland (3-2) and Italy, Switzerland and Austria (4-1) and lost to Czechia (2-3) and Croatia, Slovenia and Serbia (1-3).
As last year we struggled most on the U20 board where we do not yet have any dan players. However our U12s continue to excel in this event - we picked up wins in 6 or the 7 games played in this age group with two of our U12 players also playing up an age group on occasion.
The nominations for our Annual Awards are now closed and can be seen here: http://www.britgo.org/awards/2016
Voting is now open to our Association Members (you need to login first) and will close one week before our AGM, on 24th March.
The 42nd London Open was dominated by Sai Sun (5d) from Beijing who won three titles.
She won the Open title and £120, with six wins out of seven, won the Lightning and also the
Pair Go with
Xinchi Gong. In all 76 players took part in the event, held as usual at ISH in London.
On hand to do game analysis and lectures was the professional from Romania, Catalin Taranu (5p). He lectured on the opening and analysed the game between Andrew and Sai.