[ExI] alpha zero

[Dylan Distasio]

The code for an approximation of the Go version is freely available, but to
do the training,  you will need a lot of horsepower.

https://github.com/gcp/leela-zero

There aren't a ton of secrets in open source AI which is awesome.

On Dec 10, 2017 12:10 PM, "spike" <spike66 at att.net> wrote:

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> *On Behalf Of *John Clark
> *Subject:* Re: [ExI] alpha zero
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> On Sun, Dec 10, 2017 at 10:48 AM, spike <spike66 at att.net> wrote:
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> ​> >…Ja of course this is impressive, but consider all the ways this
> could be achieved that would look like it had trained itself from nothing
> in a day.  An eager press corps could report the program was given nothing
> but the rules of chess, when in reality it was given the StockFish chess
> engine with no opening book.  That would constitute being given chess rules
> only, if the phrase is interpreted broadly.  In fact, that would be a good
> approach to the problem: StockFish code is highly optimized already, so
> there is no need to reinvent that wheel.
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> ​
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> >…I don't think that's what they did but if it was it would be just as
> impressive… John K Clark
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> On the contrary sir.
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> Once chess software achieved a certain level, it didn’t much matter how
> good it is: an ordinary consumer-level person cannot challenge it.  I see
> little point in paying for 3345 Elo software if 3317 software is free and
> open-source.  However… if DeepMind really has something that can learn from
> self-play, that software is worth jillions of dollars.  People who don’t
> care about chess that much would buy it and experiment with it.  I would.
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> Here’s what I am doing: reading carefully what the DeepMind paper claims
> they did, and comparing with what the press is reporting.  If you have time
> to blow on what could be the most important development in singularity
> theory since Eliezer left the ExI list, do a Google search on DeepMind
> Chess AlphaZero and look at the various articles.  Note that they are
> contradictory in some ways and many of the articles make claims that the
> DeepMind paper doesn’t make exactly.  The tech-press seems to have engaged
> in some examples of what I see here, hopeful thinking.  I did it myself: I
> hope it is right, I hope a computer figured out how to perform 160 Elo
> above the current version of StockFish and did it entirely by
> self-training.  But I suspect we don’t yet have the whole story.
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> That said, I would give DeepMind a few hundred bucks for that software
> based on what I think it did.  I might give them a couple thousand if they
> would show me their source code.  If we can come to understand the
> principles we think they used for self-play learning, it should be
> applicable to any zero-sum game.  It might even be possible to extend the
> paradigm to optimization games, gambling games and non-zero-sum games such
> as Diplomacy.
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> spike
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