[mailto:computer-go-boun...@computer-go.org] On Behalf Of
"Ingo Althöfer"
Sent: Thursday, January 28, 2016 1:00 AM
To: computer-go@computer-go.org
Subject: Re: [Computer-go] Game Over
Hello Anders,
thanks for the summary on the smartgo site.
> ... the truncated rollouts mentioned in the pa
> here a comment by Antti Törmänen
> http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/
Thanks, exactly what I was looking for. He points out black 85 and 95
might be mistakes, but didn't point out any dubious white (computer)
moves. He picks out a couple of white moves a
2016-01-28 12:23 GMT+01:00 Michael Markefka :
> I find it interesting that right until he ends his review, Antti only
> praises White's moves, which are the human ones. When he stops, he
> even considers a win by White as basically inevitable.
>
> White moves are the AI ones, check the players
___
That would make my writing nonsense of course. :)
Thanks for the pointer.
On Thu, Jan 28, 2016 at 12:26 PM, Xavier Combelle
wrote:
>
>
> 2016-01-28 12:23 GMT+01:00 Michael Markefka :
>>
>> I find it interesting that right until he ends his review, Antti only
>> praises White's moves, which are t
I find it interesting that right until he ends his review, Antti only
praises White's moves, which are the human ones. When he stops, he
even considers a win by White as basically inevitable.
Now Fan Hui either blundered badly afterwards, or more promising, it
could be hard for humans to evaluate
Hi Xavier,
Really nice comments by Antti Törmänen, to the point and very clear
explanation. Thanks for the pointer.
best regards,
Jan van der Steen
On 28-01-16 11:45, Xavier Combelle wrote:
here a comment by Antti Törmänen
http://gooften.net/2016/01/28/the-future-is-here-a-professional-leve
here a comment by Antti Törmänen
http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/
2016-01-28 11:19 GMT+01:00 Darren Cook :
> > 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
> 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)
Thanks. Has anyone (strong) made commented versions yet? I played
through the first game, but it j
On 28.01.2016 04:57, Anders Kierulf wrote:
Please let me know if I misinterpreted anything.
You write "Position evaluation has not worked well for Go in the past"
but I think you should write "...Computer Go..." because applicable,
reasonably accurate theory for human players' positional eval
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
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
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/
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
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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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
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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http://comput
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
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
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
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
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
> 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
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
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
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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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
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
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