American Go E-Journal » Master/AlphaGo Commentaries

AlphaGo-AlphaGo Game 3: Three 3-3 invasions, a big moyo and a fight that fills the center of the board

Thursday August 3, 2017

This exciting game features an astonishing three invasions at the 3-3 point, prompting Michael Redmond 9p to note that “This version of AlphaGo 2017.08.03_AlphaGo vs. Alphago Game 3will invade here at any time when there is no urgent fighting going on. AlphaGo played an early invasion at the 3-3 in just two of the 60 Master series games, but that was shocking, as it defied the common knowledge of pros that such an early invasion should be bad. In this 50-game series AlphaGo played an early 3-3 invasion about 40 times.”

Click here for Redmond’s video commentary, hosted by the AGA E-Journal’s Chris Garlock, and follow along with the sgf below, which as usual includes extra variations.

“Black plays a big moyo game, and then chases an eyeless White group into Black’s moyo, to start a fight that fills the center of the board,” adds Redmond.

The video is produced by Michael Wanek and Andrew Jackson.



AlphaGo-AlphaGo Game 2; Fighting throughout, a surprising sacrifice, a final huge ko

Wednesday August 2, 2017

“In this game AlphaGo shows great flexibility in the early stages, and also its ability to calculate extremely complicated fights later in the game,” 2017.08.02_AlphaGo vs. Alphago2says Michael Redmond 9P in his commentary on Game 2 in the AlphaGo-AlphaGo self-played series. Click here for his video commentary, hosted by the AGA E-Journal’s Chris Garlock, and follow along with the sgf below, which includes the extra variations Redmond refers to in the video. “Against Black’s sanrensei, White plays two unusual moves at 10 and 16 to create a unique opening,” says Redmond. “As the fighting starts, White makes a surprising sacrifice, abandoning a group to take the offensive in the center. Fighting continues throughout the game to climax in a final huge ko.” The video is produced by Michael Wanek and Andrew Jackson.



Redmond’s AlphaGo-AlphaGo commentaries launched

Tuesday August 1, 2017

In the first in a new series of AlphaGo video commentaries, Michael Redmond 9p, hosted by the AGA E-Journal’s Chris Garlock, reviews Game 1 of the amazing AlphaGo vs. AlphaGo selfplay games. The 50-game series was published by Deepmind after AlphaGo’s victory over 2017.08.01_AlphaGo vs. Alphago with Michael Redmond 9p Game 1world champion Ke Jie 9p in May 2017. Games 2-4 will be released this week, leading up to this year’s U.S. Go Congress in San Diego, which starts on Saturday.

“In the Master series earlier this year, AlphaGo first showed its big shimaris, and often played to dominate the center of the board in the early opening, using its famous shoulder hits to do so,” says Redmond. The Master version “had an early advantage in almost all of the games,” Redmond says, “and I was impressed with its ability to simplify complicated middle game positions and bring the game to an early outcome. Less convincing was the way Master handled complicated joseki. It also had a disturbing habit of losing several points in the endgame to win by the smallest possible margin.”

“With this new self-played series,” says Redmond, “I wanted to see how these traits had survived AlphaGo’s evolution; five months is a long period of time for a self-teaching AI. The exciting news is that Alphago has changed dramatically.” Click here, to find out how in the video commentary and see below for Redmond’s extensively commented sgf file. The videos are produced by Michael Wanek and Andrew Jackson; sgf editing support by Myron Souris.




Go Spotting: AlphaGo and Beyond; Robopocalypse Now? Kubo and the Two Strings

Sunday July 23, 2017

AlphaGo and Beyond: The national security blog Lawfare last month posted an article called “AlphaGo and Beyond: The Chinese Military Looks to Future ‘Intelligentized’ Warfare,” reports Kyle Highful. “Among other things, this article discusses alleged Chinese censorship of AlphaGo’s match with Ke Jie, recent advances in American and Chinese artificial intelligence, and possible military implications of AI 2017.07.19_KuboGobreakthroughs like AlphaGo.”

Robopocalypse Now? The 2017 Summer issue of “The Bent” has an article titled “Robopocalypse Now?” that includes several paragraphs on AlphaGo as an example of the recent progress in Artificial Intelligence, reports Jeff Newmiller. The Bent is the official news magazine of the Tau Beta Pi engineering honor society“The title was a bit of fluff… the conclusion of the article is that AI is more likely to yield surprise responses to unexpected input than to purposely mislead us.”

Kubo and the Two Strings: “Last weekend I watched the movie Kubo and the Two Strings (right), released in 2016 by Laika Entertainment and currently available on Netflix,” writes Alicia Seifrid. “It is a stop-motion fantasy film set in feudal Japan.  Early in the film, the main character Kubo goes into the village, and you see the villagers going about their everyday lives, including two men playing go.  Thanks as ever for sharing so much enjoyable and interesting go news!”


In surprise announcement, AlphaGo retires; DeepMind to release 50 self-play games

Saturday May 27, 2017

AlphaGo is retiring. DeepMind’s Demis Hassabis and David Silver made the stunning announcement as the Future of Go Summit wrapped up in Wuzhen, China, saying that the match against world #1 Ke Jie represented “the highest possible pinnacle for AlphaGo as a competitive program” and would be the AI program’s final match.2017.05.27_alphago

“The research team behind AlphaGo will now throw their considerable energy into the next set of grand challenges, developing advanced general algorithms that could one day help scientists as they tackle some of our most complex problems, such as finding new cures for diseases, dramatically reducing energy consumption, or inventing revolutionary new materials,” Hassabis said. “If AI systems prove they are able to unearth significant new knowledge and strategies in these domains too, the breakthroughs could be truly remarkable. We can’t wait to see what comes next.”

DeepMind isn’t leaving the go community empty-handed, however. As a “special gift to fans of Go around the world,” DeepMind is publishing a special set of 50 AlphaGo vs AlphaGo games, which Hassabis and Silver said “we believe contain many new and interesting ideas and strategies for the Go community to explore.”

And while DeepMind doesn’t plan to give AlphaGo itself a wide release, Hassabis says he’s more than happy for others to make use of DeepMind’s research themselves. Programs like Tencent’s Fine Art and Japan’s DeepZenGo have used similar deep-learning techniques to achieve around 9th-dan level, according to Hassabis. DeepMind will soon publish another paper on how it architected the latest version of AlphaGo, AlphaGo Master, and Hassabis expects other companies to learn from the new research.

Also, Hassabis said that “We’re also working on a teaching tool – one of the top requests we’ve received throughout this week. The tool will show AlphaGo’s analysis of Go positions, providing an insight into how the program thinks, and hopefully giving all players and fans the opportunity to see the game through the lens of AlphaGo. We’re particularly honoured that our first collaborator in this effort will be the great Ke Jie, who has agreed to work with us on a study of his match with AlphaGo. We’re excited to hear his insights into these amazing games, and to have the chance to share some of AlphaGo’s own analysis too.”

Read more in The Verge and on the DeepMind website. photo courtesy The Verge


AlphaGo-Ke Jie watch parties help build AGA chapter “strength, longevity and cohesiveness”

Saturday May 27, 2017

AlphaGo-Ke-Jie surprising move copyChapters of the American Go Association held watch parties across the country for the historic AlphaGo-Ke Jie match this week. Here are a couple of reports and photos.

At the Seattle Go Center (right), 30 people came for Nick Sibicky’s lecture on a previous game by Ke Jie, and more than 40 were in the room for the first AlphaGo/Ke Jie game.

durham-sm_1970A dozen go aficionados gathered in Durham Wednesday night (left), to review and discuss Game One. A surprise guest was Cole Pruitt, the co-director and producer of “The Surrounding Game.” Says Bob Bacon, “We devoured pizza generously provided by the AGA as we witnessed another milestone in the history of go. Events like this help add to the strength, longevity and cohesiveness of the chapters and the AGA as a whole.”

photos by Brian Allen (right) and Bob Bacon (left)


AlphaGo defeats Ke Jie in Game 3 to sweep 3-0

Saturday May 27, 2017

AlphaGo completed its sweep of world number one professional Ke Jie 9P on Saturday, winning the third and final game of their match by resignation. Ke called it “one of the greatest matches that I’ve had.” The game once again showcased exciting and surprising moves from both sides, the first arising almost immediately on move 7, a four-space extension from the upper right in which AlphaGo played one space closer to 2017.05.27_ke-jie-hassabisthe corner than in the usual Chinese opening. White 20 was a counter-intuitive second-line probe into Black’s framework on the lower right, showcasing Ke Jie’s superb positional judgment.

When Ke Jie attained a local advantage in the centre, AlphaGo switched to build a powerful framework on the top that spurred White to invade. The action came to a head when Ke Jie sacrificed the territory on the upper side to AlphaGo, gaining initiative to pressure the lower left. After AlphaGo protected its group, the match proceeded towards the endgame. Ke Jie revived his stones in the upper left to take the territorial lead, but this sequence left AlphaGo just enough latitude to take control of his group in the centre, and White resigned after 209 moves.

“We held this event aiming to discover new insights into this ancient, beautiful game,” said DeepMind CEO Demis Hassabis. “I can safely say that what has taken place since Tuesday has exceeded our highest hopes. We have seen many new and exciting moves, and we also saw AlphaGo truly pushed to its limits by the great genius Ke Jie.”

Adapted from a report on DeepMind’s AlphaGo page.


AlphaGo Pair and Team Go wrap up

Friday May 26, 2017

“Playing games like this will give us new ideas about how to play,” said Gu Li 9P, after playing in the AlphaGo-Pair Go and commentating on 2017.05.26_alphago-pair-gothe Team Go event. “It felt like four painters working together on a shared canvas,” added AlphaGo Lead Researcher David Silver, “all with different styles, all combining together to make something truly beautiful.”

In Pair Go, the first of the day’s matches on Thursday, top Chinese professionals Gu Li and Lian Xiao each had their own AlphaGo teammate, alternating moves in tag team style. In the second, Team Go, five of China’s top professional Go players had the unique challenge of working together to take on AlphaGo’s distinctive style.

2017.05.26_alphago-team-goIn Pair Go, AlphaGo and its professional teammate agreed with each others’ moves – though they surprised each other from time to time too. In a sense, the match provided a glimpse of how human experts might be able to use AI tools in the future, benefiting from the program’s insights while also relying on their own intuition. The AlphaGo/Lian Xiao Pair Go team prevailed over AlphaGo/Gu Li, winning by resignation.

Team Go provided a different but no less compelling challenge, requiring players to coordinate closely to make the most of the format. The professional teammates – Zhou Ruiyang, Chen Yaoye, Mi Yuting, Shi Yue and Tang Weixing – had access to their own study board to discuss and analyse variations, allowing them to draw on centuries of Go wisdom and styles as they debated strategies. They approached the challenge in a light-hearted manner, clearly enjoying the experience of playing together, and their resulting style was very balanced. In the end, AlphaGo, once again, won by resignation.

“AlphaGo could actually broaden the horizon of Go playing,” said Lian Xiao. “It could bring more imagination into Go.”

The final game between AlphaGo and Ke Jie will be played at 10:30p EDT Friday night; DeepMind is streaming the matches live, posting match updates and expert commentaries every day on this page and on their Twitter account, @DeepMindAI. For more details, you can visit the official event page here

- adapted from a report on the DeepMind AlphaGo website


“100 percent perfection,” AlphaGo clinches match against Ke Jie, 2-0

Thursday May 25, 2017

Despite 100 moves that “were the best anyone’s ever played against the Master version,” world number 1 Ke Jie 9P was forced to resign Game 2 of his match against AlphaGo on Thursday in Wuzhen, China, clinching the best-of-3 series for the go AI. Afterwards, Ke said that he thought he “was very close to winning the match in the middle of the game” and that he was so excited “I could feel my heart thumping!” But, he admitted, “Maybe because I was too excited I made some stupid moves. Maybe that’s the weakest part of human beings.” The latest version of AlphaGo, Ke added, “is 100 percent perfection…For human beings, our understanding of this game is only very limited.”

The game was extraordinarily complex, with seven separate groups on the le2017.05.25_26googleswins-1-master768ft and lower sides, all of them interrelated and none of them settled. This type of complex interaction, impossible to calculate fully and demanding the most of each player’s value judgment and intuition, brought both Ke Jie and AlphaGo into their element.

With many groups hanging in the balance, both sides continued raising the stakes. Ke Jie played daringly, creating the possibility of sacrificing the ko and two of his groups to take AlphaGo’s two groups in the upper left on an even larger scale. However, AlphaGo chose to settle the ko and the game by connecting at move 137, conceding enormous gains to White on the lower left to secure even greater profits in the lower right. As Ke Jie, playing white, could not control the whole upper left, AlphaGo’s territorial advantage proved decisive.

“What an honor it is to play with a genius like Ke Jie,” said Demis Hassabis, CEO and co-founder of DeepMind. “This is called the Future of Go Summit, and today I think we saw a game from the future,”

Still to come are Pair and Team Go on Friday, and the third AlphaGo-Ke Jie match on Saturday. (use this Time Zone Converter to determine local dates/times)

DeepMind is streaming the matches live, posting match updates and expert commentaries every day on this page and on their Twitter account, @DeepMindAI. For more details, you can visit the official event page here. American Go Association chapters continue to play watch parties (they’re eligible for $100 in non-alcohol expenses like pizza; click here for details); email details to and we’ll post an updated report.

- adapted from a report on the DeepMind/AlphaGo site; photo by China Stringer Network, via Reuters

Other match coverage:
Google’s A.I. Program Rattles Chinese Go Master as It Wins Match (New York Times)
AlphaGo beats Ke Jie again to wrap up three-part match (Verge)
Google’s AlphaGo Continues Dominance With Second Win in China (Wired)
China censored Google’s AlphaGo match against world’s best Go player (The Guardian)


New version of AlphaGo self-trained and much more efficient

Wednesday May 24, 2017

by Andy Okun, reporting from the  ‘Future of Go’ summit in Wuzhen, China

The version of AlphaGo that defeated Ke Jie 9p in the first round of the three game challenge match yesterday was trained entirely on the self-2017.05.24_hassabis-ke-silverplay games of previous versions of AlphaGo, a Google DeepMind engineer told an audience in China.  David Silver (at right), lead researcher on the AlphaGo project, told the Future of AI Forum in Wuzhen that because AlphaGo had become so strong, its own games constituted the best available data to use.

The version of AlphaGo that beat Fan Hui 2p in 2015 (AlphaGo Fan) and the one that defeated Lee Sedol 9p last year in Seoul (AlphaGo Lee) each included a “value network,” designed to evaluate a position and give the probability of winning, and a “policy network,” designed to suggest the best next move, that were trained using hundreds of thousands of skilled human games.  The most recent version, AlphaGo Master, trained both networks on a database of its self-play games generated by its predecessors.

This was not the only new information Silver revealed about system.  The version playing Ke Jie is so much more efficient that it uses one tenth the quantity of computation that Alphago Lee used, and runs on a single machine on Google’s cloud, powered by one tensor processing unit (TPU).  AlphaGo Lee would probe 50 moves deep and study 100,000 moves per second.  While that sounds like a lot, by comparison, the tree search powering the Deep Blue chess system that defeated Gary Kasparov in the 1990s looked at 100 million moves per second.

“AlphaGo is actually thinking much more smartly than Deep Blue,” Silver said.

2017.05.24_google-deepmindIn addition, Silver revealed that DeepMind had measured the handicap needed between different versions of the software. AlphaGo Fan could give four stones to the previous best software, such as Zen or CrazyStone, which had reached 6d in strength. AlphaGo Lee, in turn, could give AlphaGo Fan three stones, and AlphaGo Master, which at the new year achieved a 60-game undefeated streak against top pros before coming to this challenge, is three stones stronger than AlphaGo Lee.  Silver delivered this with the caveat that these handicap stones are not necessarily directly convertible to human handicaps.  Professional players suggested that this may be due to AlphaGo’s tendency to play slowly when ahead — i.e., an AlphaGo receiving a three stone handicap may give its opponent ample opportunities to catch up, just as yesterday’s AlphaGo let Ke Jie get to a 0.5 point margin. This also reveals that AlphaGo is able to play with a handicap, previously a matter of speculation in the go community.

Silver’s talk came after DeepMind chief Demis Hassabis gave a passionate account of how go and AI research have fed each other. Go is so combinatorially large that playing it well is intuitive as well as a matter of calculation.  The methods that have worked so well with AlphaGO have generated moves and strategies that seem high level, intuitive, even creative. These same methods have applications in medicine, energy and many other areas. He quoted Kasparov: “Deep Blue was the end.  AlphaGo is the beginning.”

photos by Dan Maas