Not sure if this has been posted here already or not:
http://arxiv.org/abs/1511.06410
I found out about it from here, which makes sense I guess:
https://www.facebook.com/zuck/posts/10102619979696481?fref=nf
-Richard
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Yes, it has been:
http://computer-go.org/pipermail/computer-go/2015-November/008267.html
Are there any news on Google's efforts?
Álvaro.
On Wed, Jan 27, 2016 at 10:10 AM, Richard Lorentz
wrote:
> Not sure if this has been posted here already or not:
> http://arxiv.org/abs/1511.06410
>
>
https://www.youtube.com/watch?v=g-dKXOlsf98
Google beats Fan Hui, 2 dan pro, 5-0 (19x19, no handicap)!
Congratulations! I am proud of my student Aja. They'll play Lee Sedol in
March.
It's a pity they don't participate in the UEC Cup.
I read the paper. The most original idea is in learning a
This seems quite amazing. Congratulations to the Google DeepMind team and
AlphaGo!
Rémi, Is the paper of which you speak available?
Many thanks,
Erik S. Steinmetz
e...@steinmetz.org
(612) 789-6940
(612) 978-4342 cell
> On Jan 27, 2016, at 11:16 AM, Rémi Coulom wrote:
>
> https://www.youtu
http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html
well done Aja :)
On Wed, Jan 27, 2016 at 5:59 PM, Erik S. Steinmetz
wrote:
> This seems quite amazing. Congratulations to the Google DeepMind team and
> AlphaGo!
>
> Rémi, Is the paper of which you speak available?
>
> Many t
I foresee a future where we watch Google vs Facebook matches with
human professionals providing commentary on their superiors :-)
Interesting times we live in!
-John
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On 27/01/2016 18:58, Darren Cook wrote:
> P.S. Curiously the BBC ran an article today on how Facebook is getting
> close to top pro level too: http://www.bbc.co.uk/news/technology-35419141
http://googleresearch.blogspot.be/2016/01/alphago-mastering-ancient-game-of-go.html
"The match was played be
for those looking for sgfs: http://deepmind.com/alpha-go.html
2016-01-27 19:25 GMT+01:00 Julian Schrittwieser :
> Actually the paper has been in the works for quite a while and was already
> set to be released today for some weeks.
> It seems a journalist reached out to Facebook to comment a day
A member of the German forum said, that a French Go player reported on
Facebook, that Fan Hui lost 5 out of 5 games to the Google Go engine.
Now this is a lot of "x heard that y said that..." but if someone can look
into it and maybe confirm or deny that rumour, it would be great.
2016-01-27 16:19
> A member of the German forum said, that a French Go player reported on
> Facebook, that Fan Hui lost 5 out of 5 games to the Google Go engine.
To ask the obvious:
Were these even or handicap games?
-John
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Congratulations Aja, well done :)
On Wed, Jan 27, 2016 at 6:46 PM, Aja Huang wrote:
> Hi all,
>
> We are very excited to announce that our Go program, AlphaGo, has beaten a
> professional player for the first time. AlphaGo beat the European champion
> Fan Hui by 5 games to 0. We hope you enjoy o
http://wayt.synology.me/wordpress/1348-2/
no handicap
2016-01-27 17:42 GMT+01:00 John Tromp :
> > A member of the German forum said, that a French Go player reported on
> > Facebook, that Fan Hui lost 5 out of 5 games to the Google Go engine.
>
> To ask the obvious:
>
> Were these even or handica
icipate in the UEC Cup.
> > >
> > > I read the paper. The most original idea is in learning a value
> network.
> > It seems to be extremely efficient.
> > >
> > > Rémi
> > > ___
> > > Computer-
> Google beats Fan Hui, 2 dan pro, 5-0 (19x19, no handicap)!
> ...
> I read the paper...
Is it available online anywhere, or only in Nature?
I just watched the video, which was very professionally done, but didn't
come with the SGFs, information on time limits, number of CPUs, etc.
Aja, David - s
I really do hope that this also turns into a good analysis and
teaching tool for human player. That would be a fantastic benefit from
this advancement in computer Go.
On Wed, Jan 27, 2016 at 9:08 PM, Aja Huang wrote:
> 2016-01-27 18:46 GMT+00:00 Aja Huang :
>>
>> Hi all,
>>
>> We are very excited
Distributed AlphaGo is stronger than CrazyStone by +1200 Elo?!
AlphaGo: Mastering the ancient game of Go with Machine Learning
http://googleresearch.blogspot.jp/2016/01/alphago-mastering-ancient-game-of-go.html
Hiroshi Yamashita
- Original Message -
From: "Rémi Coulom"
To:
Sent: Thu
Actually the paper has been in the works for quite a while and was already
set to be released today for some weeks.
It seems a journalist reached out to Facebook to comment a day ago.
On Wed, Jan 27, 2016 at 6:19 PM, Gian-Carlo Pascutto wrote:
> On 27/01/2016 18:58, Darren Cook wrote:
> > P.S. C
If you want to view them in the browser, I've also put them on my blog:
http://www.furidamu.org/blog/2016/01/26/mastering-the-game-of-go-with-deep-neural-networks-and-tree-search/
(scroll down)
On Wed, Jan 27, 2016 at 6:28 PM, Marc Landgraf wrote:
> for those looking for sgfs: http://deepmind.co
Thank you for the game records! I really am just a by stander and
kibizer and a weak player, but isn't the style of Fan Hui going too
low positions, keep making clusters, and do a local fight at a time?
On Wed, Jan 27, 2016 at 10:29 AM, Julian Schrittwieser
wrote:
> If you want to view them in th
Congratulation! Really an excellent job, David and Aja!
I imagined once but didn't think such value networks can be trained in
practice, what a suprising machine power of the cloud!
Hideki
Remi Coulom: <56a919e2.9030...@free.fr>:
>https://storage.googleapis.com/deepmind-data/assets/papers/dee
https://storage.googleapis.com/deepmind-data/assets/papers/deepmind-mastering-go.pdf
On 01/27/2016 06:58 PM, Darren Cook wrote:
Is it available online anywhere, or only in Nature?
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Hello Aja,
congratulations to the success of you and the other team member!
To the others: Should we call the game "Goo" in the future,
to honour Goo-gles progress?
CHeers, Ingo.
Gesendet: Mittwoch, 27. Januar 2016 um 19:46 Uhr
Von: "Aja Huang"
An: computer-go@computer-go.org
Betreff: [Comp
Congratulations Aja and David!
What an interesting idea to train the value network and surprising power
of the cloud!
Then, when you will get +400 Elo? :)
Hideki
Aja Huang:
:
>Hi all,
>
>We are very excited to announce that our Go program, AlphaGo, has beaten a
>professional player for the f
2016-01-27 18:46 GMT+00:00 Aja Huang :
> Hi all,
>
> We are very excited to announce that our Go program, AlphaGo, has beaten a
> professional player for the first time. AlphaGo beat the European champion
> Fan Hui by 5 games to 0. We hope you enjoy our paper, published in Nature
> today. The pape
Sorry for a typo. I meant
> Hello Aja,
>
> congratulations to the success of you and the other team memberS!
So, not singular, but plural.
Ingo.
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Congratulations Aja.
Do you have a plan to run AlphaGo on KGS?
It must be a 9d!
Yamato
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Wow, excellent results, congratulations Aja & team!
I'm surprised to see nothing explicitly on decomposing into subgames (e.g.
for semeai). I always thought some kind of adaptive decomposition would be
needed to reach pro-strength... I guess you must have looked into this;
does this mean that the
Congratulations people at DeepMind :-)
I like the fact that alphaGo uses many forms of learning (as humans do!):
- imitation learning (on expert games, learning an actor policy);
- learning by playing (self play, policy gradient), incidentally generating
games;
- use of those games for teaching a
Congratulations to Aja!
A question to the community. Is anyone going to replicate the experimental
results?
https://www.quora.com/Is-anyone-replicating-the-experimental-results-of-the-human-level-Go-player-published-by-Google-Deepmind-in-Nature-in-January-2016
?
Jason
On Thu, Jan 28, 2016 at 9:
It's in the paper: "ladder capture" and "ladder escape" are features that
are fed as inputs into the CNN.
Álvaro.
On Wed, Jan 27, 2016 at 6:03 PM, Ryan Grant wrote:
> To the authors: Did the deep-NN architecture learn ladders on its own,
> or was any extra ladder-evaluation code added to the
To the authors: Did the deep-NN architecture learn ladders on its own,
or was any extra ladder-evaluation code added to the playout module?
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Really nice result! Congratulations to the team.
Now off to study the paper instead of the blogs ...
René
On Wed, Jan 27, 2016 at 3:13 PM, Jason Li wrote:
> Congratulations to Aja!
>
> A question to the community. Is anyone going to replicate the experimental
> results?
>
>
> https://www.quora
Congratulations to Aja $ DeepMind to that great result!
I am curious to see AlphaGo having to play a tough narrow endgame. In the
first of the 5 games it could affort not to play totally optimal in the end
and in the next 4 games Fan resigned. End games require again other, more math like
skill
Congratulations to Aja & DeepMind team! Amazing results :)
Yuandong Tian
Research Scientist,
Facebook Artificial Intelligence Research (FAIR)
Website:
https://research.facebook.com/researchers/1517678171821436/yuandong-tian/
Congrats to the AlphaGo team — a tremendous accomplishment!
I've been reading the paper and have written up a summary of what they did:
https://smartgo.com/blog/google-alphago.html
Please let me know if I misinterpreted anything. Also, the truncated rollouts
mentioned in the paper are s
Hello Anders,
thanks for the summary on the smartgo site.
> ... the truncated rollouts mentioned in the paper are still unclear to me.
The greatest expert on these rollouts might be Richard Lorentz.
He applied them successfully to his bots in the games Amazons (not to be mixed
up
with the onlin
Click here for the slides of Richard's talk:
https://acg2015.files.wordpress.com/2015/07/lorentz.pdf
Ingo.
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Congratulations to the researchers!
On 27.01.2016 21:10, Michael Markefka wrote:
I really do hope that this also turns into a good analysis and
teaching tool for human player. That would be a fantastic benefit from
this advancement in computer Go.
The programs successful as computer players mo
Google’s breakthrough is just as impactful as the invention of MCTS.
Congratulations to the team. It’s a huge leap for computer go, but more
importantly it shows that DNN can be applied to many other difficult problems.
I just added an answer. I don’t think anyone will try to exactly repli
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