
AIs Have Mastered Chess. Will Go Be Next? (2014) - apsec112
http://spectrum.ieee.org/robotics/artificial-intelligence/ais-have-mastered-chess-will-go-be-next
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andreyk
Related, from 2012 "Computers are very good at the game of Go " (from the
perspective of an amateur Go player):
[http://blog.printf.net/articles/2012/02/23/computers-are-
ver...](http://blog.printf.net/articles/2012/02/23/computers-are-very-good-at-
the-game-of-go/)

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ktRolster
Wow, based on this graph from the article, it's not surprising that Go
computers are competitive with top humans now:

[http://spectrum.ieee.org/image/MjUxNjkxNQ](http://spectrum.ieee.org/image/MjUxNjkxNQ)

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nsajko
I don't think that graph makes much sense.

The labels "Grand Master", "Master", "average club player" apply to Chess, not
Baduk; and the vertical dimension in the graph seems arbitrarily chosen.

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andreyk
I think the scaling is roughly reasonable. In chess National Master is is ELO
2200–2399, and above that is Grand Master, with lower ELO being skilled and
club players. In Go, 0-30kyu is amateur (club player trough master), 1-7 dan
is advanced amateur (basically master, based on there being few in this
category), and 1-9p is grand master. Based on that the graph accurately
portrays the rise of Go AIs up to 2011: Year KGS Rank 2009 1-dan 2010 3-dan
2011 4-dan 2012 5-dan

The scaling is not exact but I think it conveys the basic facts correctly - by
2011/2012 there well Go programs that could play well better than the average
club player.

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srean
One aspect that I miss in these conversations is that of energy use. Brain
sure is a energy hungry organ in our body but it still quite small compared to
say IBM's Watson. In this particular case I agree with Chomsky. Watson is as
impressive as a huge steam roller. I am positively impressed by Watson, but I
want to be impressed on different axes as well.

I am curious if a program running on a energy limited device would be able to
beat a high ranked chess grandmaster in a standard competition setting (by
that I mean the same rules about time etc). My hunch is that the answer is
still a resounding no.

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kotach
chess grandmaster can easily be beat by a smartphone app (komodo), is
smartphone using more energy than a human brain?

the problem with Go is that there's little data and the game is more complex -
but given the small sizes of the deepmind NNs if they generate billions of
meaningful games, they could probably compress their model and require less
searching thus less energy

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chongli
An adult male needs around 2500 kcal per day. This works out to 2906Wh. The
battery in a Nexus 5 is around 8Wh, for comparison. The question then becomes:
how many hours would the battery last running the Komodo 9 engine full-out?

That would be an interesting matchup. I bet a grandmaster could play slow
enough to kill the battery on the phone. A human could go a day without eating
no problem. There's no way the phone could go a day without charging while
running 100% CPU.

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gus_massa
A normal chess match last about 4 hours. If we divide proportionally the
energy of the day, that will be about 400Wh. I remember a factoid that says
that the brain consume the 20% of the energy of the body at rest (less % while
running) (more % while thinking?), so if we cut the unnecessary stuff [0] that
will be 80Wh, i.e. 10 batteries. Probably the phone is more efficient.

[0] Don't try this at home.

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chongli
So 10 batteries... how long do you think the engine could last on one battery?
Then we multiply that number by 10 and see if it's less than 4 hours... hmmm

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randcraw
Now that AlphaGo has mastered Go, this article begs the question: where does
AI go from here? Are there other high profile games to defeat, or has
competition based AI run out of opponents?

This question must have arisen within Google (and Facebook). Certainly IBM
will tell you (under duress) that neither chess nor Watson were the game
changers they had hoped, at least commercially.

If you're Larry Page, what do you do with DeepMind now?

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brightball
If I'm Larry Page and I really want to get great press for DeepMind - you use
it to combat spam and phishing.

Specifically, you code it to engage and waste the time of the people on the
other side of those scams to waste their time with false positives that they
believe to have been hooked by the system. The scammers are working too and
everything depends on ROI. If they are having to invest more and more time the
returns stop being worth it.

If you can teach an AI to do that, you can fix one of the web's biggest
nuisances.

~~~
shogun21
Gmail does a pretty good job at spam detection. Without going out of my way, I
haven't seen a spam email in years.

~~~
chongli
I rarely see spam as well. I have had quite a few false positives though.

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abecedarius
Interesting for no mention at all of machine learning, beyond "To date, there
have been no truly successful approaches to machine learning in this sphere"
["general game playing" rather than specific games like checkers]. Deep
learning was already red hot, and on my radar, yet I wouldn't have thought
this a strange omission at the time.

~~~
ZenoArrow
It depends on what is meant by machine learning. If it's referring to learning
games from first principles, then it's certainly true for the time. As far as
I know the first AI to be able to learn multiple games from first principles
was demonstrated in 2015:

[http://www.wired.co.uk/news/archive/2015-02/25/google-
deepmi...](http://www.wired.co.uk/news/archive/2015-02/25/google-deepmind-
atari)

AlphaGo wouldn't fit in this mould, as it has been taught how to win at Go
rather than working it out from the basic rules, so AI hasn't 'beaten' Go
fully, but AlphaGo is a great achievement nonetheless.

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tetraodonpuffer
it must be exciting for pros now that computers have caught up, it is always
fun to play somebody better than you at whatever game as it pushes you to
improve, and if you're a top level pro opportunities for that seems they would
be few and far between, so having a computer opponent always available to try
ideas on and help you train would be really good.

I just hope that somebody will try their hand at writing software around the
engine that dumbs down their play in a "human way", to make beginners and
intermediate players benefit also, I wonder if due to the way it works it is
possible to do this better than in chess where it doesn't seem engines that
play "convincing human strong amateur" play really exist yet

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mikeyouse
Michael Redmond was talking on the broadcast last night about his childhood
and attempting to learn to play Go. He lived in Santa Barbara but nobody near
him played Go whatsoever, so he would have to drive hours to L.A. to Koreatown
/ Japantown when they held tournaments. He also had to regularly fly to NYC to
play.

All of the difficulty in finding regular matches is what prompted him to move
to Japan and become an 'apprentice' (apologies if this isn't the correct
terminology). He eventually became extremely proficient and is a 9-dan player
now.

One wonders how good he might have become if he had access to the internet to
play against other strong players from a young age. One further wonders how
good he might have become if he could play against an AI of Alphago's
capability.

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ominous
This kind of article is interesting, revisiting predictions.

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explorer666
Where are all the "Betteridge's law of headlines" fanboys now?

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halviti
[https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...](https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headlines)

Betteridge's law of headlines is intended as a humorous adage rather than
always being literally true.

~~~
hughperkins
Well, i think, at that time, they thought the answer was: 'no'

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nsxwolf
Is war fighting next?

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matt_wulfeck
I have a hard time being impressed by the win. What's the major difference for
writing a go AI versus checkers? Doesn't it really come down to the amount of
"if/else" that can be processed in time? To me this is a bigger feat for
enclosed, non-networked processing than for AI.

Some things are not as simple as playing out every possible solution and
picking the optimal one. Art and humor, for example. It takes intelligence to
operate and judge subjectively, not compute power.

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shogun21
The difference in Go is the sheer size of the game complexity. There are too
many possible moves to calculate every action in "if/else" statements.

The AI Google created uses a combination of different learning algorithms
(supervising it by teaching known Go patterns and playing it against itself
millions of times to learn new strategies).

Checkers is a solved game. There is a best move for each play and we just
needed to build/process that giant decision tree. Go was a completely
different beast, so it's pretty significant we found an algorithm that can
beat a world class player.

