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“Surrounding Game” launches screenings worldwide

Thursday May 25, 2017

“The Surrounding Game” is coming to a theater near you! The documentary team has just announced a summer lineup of screenings in major2017.05.24_ScreeningTourList cities across the US and Europe. The screening tour includes stops in: Toronto (6/10), San Francisco (6/10-11), Boston (6/28), New York City (6/29), Barcelona (7/07), The International Chess & Games Festival in Pardubice, Czech Republic (7/14), Berlin (7/18), Amsterdam (7/20), the European Go Congress in Oberhof, Germany (7/24), and the US Go Congress in San Diego, CA (8/05).

2017.05.24_surrounding-24x36-laurels_smallTickets are on sale now and the filmmakers urge those interested to “get yours now before they sell out!”

If you don’t see your city on the list, don’t worry – you can sign up to host a screening in your community. The film is now available to screen in theaters and community spaces. “We’re offering two options for volunteers to host a screening on their own” explains director/producer Will Lockhart. “ If you have a venue in mind, you can order a community screening pack, which will provide all the tools to host a successful event. Or, if you’re keen on getting the film to play in a local theater, you can sign up with our partners at Tugg. If you gets enough RSVPs, they’ll arrange to put the film in a local theater.” The team reports that several community screenings hosted by local go groups are already in the works.

“We’ve gotten a really positive response from non-players so far,” says producer Cole Pruitt, “and we feel this is the best way to share Go with people outside the community – by not just teaching the game, but telling a story. So if your club is looking for a way to bring more people in, I encourage you to host! I believe this is our chance to bring the world of go to the world at large.”

If your club wants to host a screening of the film, click here or contact the team directly at screenings@surroundinggamemovie.com.

photos: Berlin venue, San Francisco venue, film poster

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Categories: Go Art,Main Page,World
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“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 journal@usgo.org 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)

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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

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AlphaGo-Ke Jie viewing parties update

Tuesday May 23, 2017

AlphaGo-Ke Jie viewing parties continue this week at the National Go Center in Washington DC (Center opens at 7p Wednesday; match at2017.05.23_dc-alphago 10:30pm EDT); the Seattle Go Center will be open late again Wednesday night as well (schedule is on their calendar), and the Triangle Go Group will host an AlphaGo viewing party on Wednesday evening at the EcoLounge at Recyclique, 2811 Hillsborough Rd, in Durham.

New events include:
The UCLA Go Club in Los Angeles is hosting a viewing party this Friday, May 26 at UCLA, Dodd Hall, room 175 (315 Portola Plaza, Los Angeles, CA 90095). “Anyone is welcome to join,” says Isaac Deutsch. “We are hoping to have some lively discussions during the final game!”
The Boulder Go Center will host an AlphaGo Viewing Party on May 27 in Denver, CO. Contact Stu Horowitz at stuart590@earthlink.net 720-289-6927 for details.

Myungwan Kim will stream live game commentary Thursday night on the AGA’s YouTube channel, starting at 11PM PST.

Got party? Email us at journal@usgo,org!

photo: at the National Go Center Monday night; photo by Chris Garlock

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Ke Jie: AlphaGo “like a god of Go”

Tuesday May 23, 2017

Excerpted and adapted from a report in The New York Times 

“Last year, (AlphaGo) was still quite humanlike when it played,” said Ke Jie 9P after the first match against the go-playing AI Tuesday. “But this year, it became like a god of Go.”
“AlphaGo is improving too fast,” Ke said in a news conference after the game. “AlphaGo is like a different player this year compared to last 2017.05.23_24alphago-master768year.”
Mr. Ke, who smiled and shook his head as AlphaGo finished out the game, said afterward that his was a “bitter smile.” After he finishes this week’s match, he said, he would focus more on playing against human opponents, noting that the gap between humans and computers was becoming too great. He would treat the software more as a teacher, he said, to get inspiration and new ideas about moves.
Chinese officials perhaps unwittingly demonstrated their conflicted feelings at the victory by software backed by a company from the United States, as they cut off live streams of the contest within the mainland even as the official news media promoted the promise of artificial intelligence.
2017.05.23_AlphaGO_hassabis

Excerpted from Wired 
This week’s match is AlphaGo’s first public appearance with its new architecture, which allows the machine to learn the game almost entirely from play against itself, relying less on data generated by humans. In theory, this means DeepMind’s technology can more easily learn any task.
Underpinned by machine learning techniques that are already reinventing everything from internet services to healthcare to robotics, AlphaGo is a proxy for the future of artificial intelligence.
This was underlined as the first game began and (DeepMind CEO Demis) Hassabis (in photo) revealed that AlphaGo’s new architecture was better suited to tasks outside the world of games. Among other things, he said, the system could help accelerate the progress of scientific research and significantly improve the efficiency of national power grids.

DeepMind Match 1 wrap up
2017.05.23_ke-jie-hassabis“There was a cut that quite shocked me,” said Ke Jie, “because it was a move that would never happen in a human-to-human Go match. But, afterwards I analyzed the move and I found that it was very good. It is one move with two or even more purposes. We call it one stone, two birds.”
“Ke Jie started with moves that he had learned from the Master series of games earlier this year, adding those new moves to his repertoire,” said Michael Redmond 9P. “Ke Jie used the lower board invasion point similar to AlphaGo in the Masters games, and this was a move that was unheard of before then. Although this was one of the most difficult moves for us to understand, in the last month or players have been making their own translations and interpretations of it.”
“Every move AlphaGo plays is surprising and is out of our imagination,” said Stephanie Yin 1P. “Those moves completely overthrow the basic knowledge of Go. AlphaGo is now a teacher for all of us.”

photos: (top) courtesy China Stringer Network, via Reuters (middle) Noah Sheldon/Wired (bottom) DeepMind

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Problem of the Week

Finding the Followup

Black to play