Hi!

On Mon, Feb 01, 2016 at 09:19:56AM +0000, Darren Cook wrote:
> > someone cracked Go right before that started. Then I'd have plenty of
> > time to pick a new research topic." It looks like AlphaGo has 
> > provided.
> 
> It seems [1] the smart money might be on Lee Sedol:
> 
> 1. Ke Jie (world champ) – limited strength…but still amazing… Less than
> 5% chance against Lee Sedol now. But as it can go stronger, who knows
> its future…
> 2. Mi Yuting (world champ) – appears to be a ‘chong-duan-shao-nian (kids
> on the path to pros)’, ~high-level amateur.
> 3, Li Jie (former national team player) – appears to be pro-level. one
> of the games is almost perfect (for AlphaGo)
> 
> 
> On the other hand, AlphaGo got its jump in level very quickly (*), so it
> is hard to know if they just got lucky (i.e. with ideas things working
> first time) or if there is still some significant tweaking possible in
> these 5 months of extra development (October 2015 to March 2016).

  AlphaGo's achievement is impressive, but I'll bet on Lee Sedol
any time if he gets some people to explain the weaknesses of computers
and does some serious research.

  AlphaGo didn't seem to solve the fundamental reading problems of
MCTS, just compensated with great intuition that can also remember
things like corner life&death shapes.  But if Lee Sedol gets the game to
a confusing fight with a long semeai or multiple unusual life&death
shapes, I'd say based on what I know on AlphaGo that it'll collapse just
as current programs would.  And, well, Lee Sedol is rather famous for
his fighting style.  :)

  Unless of course AlphaGo did achieve yet another fundamental
breakthrough since October, but I suspect it'll be a long process yet.
For the same reason, I think strong players that'd play against AlphaGo
would "learn to beat it" just as you see with weaker players+bots on
KGS.

  I wonder how AlphaGo would react to an unexpected deviation from a
joseki that involves a corner semeai.

> [1]: Comment by xli199 at
> http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/
> 
> [2]: When did DeepMind start working on go? I suspect it might only
> after have been after the video games project started to wound down,
> which would've Feb 2015? If so, that is only 6-8 months (albeit with a
> fairly large team).

  Remember the two first authors of the paper:

  * David Silver - his most cited paper is "Combining online and offline
    knowledge in UCT", the 2007 paper that introduced RAVE

  * Aja Huang - the author of Erica, among many other things

  So this isn't a blue sky research at all, and I think they had Go in
crosshairs for most of the company's existence.  I don't know the
details of how DeepMind operates, but I'd imagine the company works
on multiple things at once. :-)

-- 
                                Petr Baudis
        If you have good ideas, good data and fast computers,
        you can do almost anything. -- Geoffrey Hinton
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