Bronstein's stunningly brilliant Kings Indian Queen Sac concept tested between Leela and Stockfish

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Info about Leela Zero:
en.wikipedia.o...
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Leela Chess Zero (lc0) is a free, open-source, and neural network-based chess engine and distributed computing project.
Leela Zero's algorithm is based on DeepMind's 2017 paper about AlphaGo Zero.[3][6] Unlike the original Leela, which has a lot of human knowledge and heuristics programmed into it, Leela Zero only knows the basic rules and nothing more.[7]
Leela Zero is trained by a distributed effort, which is coordinated at the Leela Zero website. Members of the community provide computing resources by running the client, which generates self-play games and submits them to the server. The self-play games are used to train newer networks. Generally, over 500 clients have connected to the server to contribute resources.[7] The community has provided high quality code contributions as well.[7]
Leela Zero finished third at the BerryGenomics Cup World AI Go Tournament in Fuzhou, Fujian, China on 28 April 2018.[8]
Info about Alphazero:
en.wikipedia.o...
AlphaZero is a computer program developed by the Alphabet-owned AI research company DeepMind, which uses an approach similar to AlphaGo Zero's to master not just Go, but also chess and shogi. On December 5, 2017 the DeepMind team released a preprint introducing AlphaZero, which, within 24 hours, achieved a superhuman level of play in these three games by defeating world-champion programs, Stockfish, elmo, and the 3-day version of AlphaGo Zero, in each case making use of custom tensor processing units (TPUs) that the Google programs were optimized to make use of.[1] AlphaZero was trained solely via "self-play" using 5,000 first-generation TPUs to generate the games and 64 second-generation TPUs to train the neural networks, all in parallel, with no access to opening books or endgame tables. After just four hours of training, DeepMind estimated AlphaZero was playing at a higher Elo rating than Stockfish; after 9 hours of training, the algorithm decisively defeated Stockfish 8 in a time-controlled 100-game tournament (28 wins, 0 losses, and 72 draws).[1][2][3] The trained algorithm played on a single machine with four TPUs.
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Relation to AlphaGo Zero
Further information: AlphaGo Zero
AlphaZero (AZ) is a more generalized variant of the AlphaGo Zero (AGZ) algorithm, and is able to play shogi and chess as well as Go. Differences between AZ and AGZ include:[1]
AZ has hard-coded rules for setting search hyperparameters.
The neural network is now updated continually.
Go (unlike Chess) is symmetric under certain reflections and rotations; AlphaGo Zero was programmed to take advantage of these symmetries. AlphaZero is not.
Chess can end in a draw unlike Go; therefore AlphaZero can take into account the possibility of a drawn game.
AlphaZero vs. Stockfish and elmo
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[@kingscrusher]

Q. Can Neural networks and AB engines help test amazing opening innovations? 🤔😀😎🌍 Video: goo.gl/B3EYJK Replayable game: goo.gl/xBDb4e #chess #chessgame #ArtificialIntelligence #AI #MachineLearning #DeepLearning

[@Stockfish1511]

Sf showing once again what it is capable of. Stubborn engine, does not want to lose the final lol

[@shaun215]

Excellent presentation, thanks! It'd be great to see how these top engines handle Nezhmetdinov's stunning opening Queen sac (vs Chernikov - originally covered by KC's channel - also well worth viewing!)

[@spiritualphysics]

deep stuff... calls for a second watch... thanks for sharing..... yes chess love

[@TheAfroNoah]

beautiful game

[@kingscrusher]

Cheers, K

[@piyushsharma5938]

Thorn pawn doesn't always work gurrrllll....... It's stockfish babe

[@dannygjk]

Probably unsound sac, that doesn't help.

[@Andrey.Balandin]

KC, great stuff! Are you thinking about doing an analysis of all decisive TCEC 14 games? I know you have analysed some of them already.... but it seems to be quite a fascinating story, with Leela taking a two point lead at some point in the match only to blow it... Is there a pattern you can discern? Is there a certain character to positions or openings that Leela seems to be good at currently, that you can identify?

[@mamago92]

Incredible!

[@dannygjk]

No surprise that this sac between engines/AI ends in a win for black.

[@jamesavery3559]

deep game, thank you for the post.

[@kingscrusher]

Cheers, K

[@herzwatithink9289]

Seems like f5 was key for Black here, after which you could probably make the case that he doesn't stand worse, if not better. This was a fantastic game no doubt, but (on cursory analysis) it's hard to think White wouldn't have retained a healthy edge if she'd played Qf2 rather than Ke2, i.e if the book had ended a move sooner, as I can't imagine anyone watching believes the sac is sound. Seeing Stockfish do what Stockfish does best is always great, but (maybe like KC) I was left feeling unsure as to how much of a sporting contest this really was.

[@curtisblanco4029]

Please show on the screen which side is which. For example if Stockfish vs Leela, then show which side Stockfish and which side is Leela. It's frustrating most of the time that you don't do this.

[@dannygjk]

The convention is that the first name is white altho the video uploaders don't always do that.

[@ubednizamani5396]

What's the overall score in the match?

[@davedevosbaarle]

It's 50-49 in Stockfish's favour and the last game is being played right now.

[@TheSmkngun]

I miss your old 10 minute long format videos.

[@hgabreu]

I like the slightly longer format, going into more variants

[@TheSmkngun]

@@hgabreu Time can be a luxury for some unfortunately.

[@Bobby-fj8mk]

Sac of your Queen in the opening? Sounds too risky to me.

[@romankusnir45958]

There are too many too dangerous variations for white right from the very beginning. And not even one danger one for black. No miracle that black finally got that win from absolutelly winning opening.

[@user-ts2co4ov5h]

I much prefer games between humans