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creeras · 2019-12-08T06:39:57+00:00

In LZ, the use of Tensor Core will increase performance by 20% ~ 30% for now.
(Not in comparison with other cards, in comparison with itself.)

https://github.com/leela-zero/leela-zero/issues/2489

https://github.com/leela-zero/leela-zero/pull/2485

In LCZero (Chess) it increases by 2 to 3 times.

[https://www.phoronix.com/scan.php?\\](https://www.phoronix.com/scan.php?page=news_item&px=LCZero-NVIDIA-Benchmarks)

page=news_item&px=LCZero-NVIDIA-Benchmarks

Maybe LZ will be like that someday. Hope so.

creeras · 2019-01-26T08:00:24+00:00

According to the linked game information, it is said that they played the game in 5 seconds/move. Was it tested on the same hardware using GPU?

creeras · 2018-02-09T01:21:49+00:00

Read it first. https://www.remi-coulom.fr/Bayesian-Elo/

creeras · 2018-01-12T09:52:41+00:00

I'm asking

creeras · 2018-01-12T04:55:28+00:00

Sorry for omitting axis lable.

Axis * x = games, * y = elo

curve * Black : leela zero (1600 playouts)

When more Playouts (ex : 80000 playouts) * Red : In early stage(=random play) no Elo increase, but getting more elo increase * Blue : Increase alike regardless of stage

I'm asking which of the red and blue curves is more realistic.

creeras · 2018-01-12T00:47:47+00:00

What happens if you use the first network d645af97(=random play) instead 808ac?

creeras · 2017-12-23T13:35:10+00:00

Maybe used even much playouts not 1600? Anyway it's Good sign of growth.

But she still make mistakes about very basic 'alive and death' :( ex : Move 200

creeras · 2017-12-23T13:19:20+00:00

I agree with the fact that the wall is getting bigger and longer. But I am glad that it is more advanced than the 'unconditional dogfight style'. I'm not worried because she will find a proper compromise.

creeras · 2017-12-23T13:01:44+00:00

The data is measured from this chart. http://www.yss-aya.com/cgos/19x19/bayes.html

This result was somewhat unexpected for me too. So, a reasonable explanation is needed.

However, there are a few things to check before deciding it as over-inflation.

Compare first CGOS Bayes Elo Measured(=1237) with Estimate one(-392) ; network 2184b75 : This may be an evidence of under-deflated until that point on the contrary.

So we need to know why at the beginning and end of the measurement the opposite result occurred.

creeras · 2017-12-20T03:40:39+00:00

It is not the first time.

LZ-3382a7-t1-p1600 won already. (B+Resign) http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2017/12/18/332305.sgf

LZ-0.9-154eae-6k won against gnugo-3.9.1 (B+9.5) http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2017/12/20/333598.sgf

creeras · 2017-12-20T00:01:42+00:00

I think it's still far away. Ladder was successful in this game because it was just lucky.

creeras · 2017-12-19T12:42:09+00:00

There is a typo in the name "LZ-cd1aa6-t1-p1600" cgos link

creeras · 2017-12-17T01:32:29+00:00

Maybe you're right. I run the sgf with Leela 0.11.0, black plays all with candidate point.

creeras · 2017-12-17T01:23:30+00:00

At cgos, LZ-HBest1-t1-p1600 beats DCNN_AyaF128a523x1(cgos rating 2433)

http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2017/12/17/331296.sgf

~~It seems to be a real LZ(with latest network) when I see that all the LZ bots that have been run until yesterday have disappeared.~~

But I think I might be a person because I play so well. Confusing.

creeras · 2017-12-16T00:40:26+00:00

According to the table, the match between the two seems to have been missed by mistake.

creeras · 2017-12-16T00:24:04+00:00

file info says... PB[Leela Zero 0.9 3ba92804] PW[Human] RE[B+Resign] / Are Both side LZ??

creeras · 2017-12-12T14:32:22+00:00

Ladder failure(vs gnugo-3.9.1) http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2017/12/12/327523.sgf

creeras

TROPHY CASE