I think it's a test by pookpooi actually.

The most interesting would probably be to run Leela with 1 cpu and no GPU. Then we know how much the GPU is worth. I'm not sure it affects the conclusion vs Zenith because Zenith can't use the GPU anyway, but that is not Leela's fault.

Zen 14.0 is now also on CGOS!

If it was test by me I wouldn't use gpu in the first place

not true, he was right

(Leela 0.8 was not stronger than Zenith 6)

Leela 0.9.0 defeats Zen again (this time without pondering, still using much more time than Zen)

Zenit Go 6 [setting: 20 seconds per move]
Leela 0.9.0 GPU [setting: 20 minutes for the game] (used more than 40 minutes)

CPU Intel 2500K GPU Nvidia GTX 970

Leela's advice towards Zen: Move 91 should have been at J10. Zen looses with an empty triangle (52% => 47% win)
Zen was still quite sure to win the game at this time (60% win)

This is a typical diagramm of an opening I play with pretty good success. After analyzing it for 20 minutes, Leela gives it only about 41.5% for White with the slow 'a' as best continuation for White. I am interested in what CS or Zen say to this position, and how they would continue for White. I usually continue with 'b' or 'c'.

Click Here To Show Diagram Code

[go]$$B
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$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . O . . O . . . X . . . . . |
$$ | . . . X . . . . . , . . . . . X . a . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . O . . |
$$ | . . X . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . , . . . . . , . . . . . b . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . c . . |
$$ | . . X . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . X . . . . . , . . . . . O . . . |
$$ | . . . . . O . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ | . . . . . . . . . . . . . . . . . . . |
$$ +---------------------------------------+[/go]

Given that you are 5D, can't you just play this out vs Leela, and see what happens after a bunch of moves? Either it'll show you a refutation, or its score will go towards 50%.

Zen suggest k4 with 53% for white. But I'd rather trust Leela. If you look more closely at its Net Win %, it says w is winning by 28% (i.e. losing the game) which is, I believe, more accurate than Win %. At least that's what those Deep Mind guys were looking at when they were testing AlphaGo.

Interesting. How can there be such a difference between the two probabilities?

I rechecked and here is what Leela says in detail: D2(best move): Win% 42, MC win% 51.7, Net win% 31.8, Net prob% 29. What is the meaning of all these numbers anyway? I always thought that win% matters, the rest not so much.

Did everyone set the same komi, and ensure the different bots all respect it?

BTW, I like "a". It is pretty much sente, and after White "b", instead, it is a good point for Black.

_________________
The Adkins Principle:
At some point, doesn't thinking have to go on?
— Winona Adkins

Visualize whirled peas.

Everything with love. Stay safe.

It's explained on Leela's webpage.

FAQ: "What do the columns in the Analysis Window mean?"

Is it possiple to use 4x nvidia geforce gtx 1080 with Leela?
And how big is the benefit from 1 to 2 to 4 gpus? +1, +2, +4 Dan

How is Net win % and Net Prob win % calculated? What does Leela do (in simple words)? For example, in MC win%, Leela is just playing many random games and e.g. if Black wins 6000 out of 10.000 random games it will give Black 60% winrate.

Its a bit like human intuition. That net looked at millions of positions and who was winning in the end, and learned to develop an intuition saying "this looks like black is going to win" or "this looks like its still even". This intuition thinks black is likely to win from here(probably the net was trained with pro games or strong amateur games(KGS? I know Alphago started out with KGS games), maybe also with selfplay-games of Leela, I dont know.

haylee playing leela 0.9 :

https://www.youtube.com/watch?v=FFU7pEEMAjU

sadly not on optimal hardware and also recording while actually playing (instead of just reviewing her game or something like that).

hopefully she plays leela again under better conditions
still a cool video!

So basically its intuition depends on the quality of the database used, interesting. Obviously the AI has to look at my pattern and compare it with the same or similiar patterns of all the database games, and then look to how these games went. Is there any structure of how this pattern-searching and -matching goes or is this what they call "black box"?

I'm relly no expert there, so dont think that what I say is neccessarily correct, but it seems to be the general question how a neural network work, so you might want to read up on that(https://en.wikipedia.org/wiki/Artificial_neural_network). In general it tries so simulate the way a human brain works. Some go realted neural network usualy gets 19x19 "neurons" and has interconnections between them, that get more or less important as the net evolves and learns which connections between the intersections on the board are important and which arent.

If you do it a little more carefully, you probably have more than one layer with 19x19 neurons, so that not only the positions of the Stones(black/white/none) can be input, but also proprocessed information(can you capture there/is there a ladder there/ is a move there lagal), so that the net doesnt have to learn those things on its own(for example figuring out the rule "if that move captures a lot of stones, its probalbly good", is much easier to implement if you get an input point that tells you "capture here" and you dont have to combine the stones postion to find that out on yourself without someone telling you the capture rule).

At least AlphaGo has two of those nets, one to prdict, where the next move might be, and one to predict, who is likely to win, I suppose its the same with Leela, the first one being responsible for "NetProb"(how likely does it think a next move there is), the other one for "Net Win"

However, Leela enjoyed a lot of pondering time because she talked a lot.

Wild card was offered to Leela from UEC organizers, does this mean it'll participate there as well.

Why sadly not on optimal hardware?

For example
-can Leela use 2x xeon???
-can Leela use 2x gpus???

I actually have plans to buy 4x and 4x in some months.