Highly Evolved Anti (Stock) Fish plays a shockingly remarkable queen sacrifice in French Defence

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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 be helpful to eradicate weaknesses in traditional software? 🤔😀😎🌍 Video: bit.ly/2IrbX0f Replayable game: bit.ly/2GtMSzu #chess #chessgame #ArtificialIntelligence #AI #MachineLearning #DeepLearning #TailoredAI #TailoredNN #TailoringAI Antifish / Beta one Discord: discordapp.com/channels/435943710472011776/499544336266952704

[@julioandresgomez3201]

Highlight the specific drawbacks, yes, eliminate them altogether, most likely not, like a wheel with less soil friction runs faster, more efficiently, but with no friction at all it could not move forward, only spin endlessly.

[@yotoober1]

yes, but this process again will prove to be 'chasing a ghost'...as while it is entirely possible to develop software to find 'holes' in stockfish's evaluation method, again, the answer would be to increase hash and clockspeed and to 'patch' the hole. as again, chess is a 'finite' possibility game, it should not be too difficult to patch the holes found and make stockfish still stronger. all that need be done is to find the BOOM move and evaluate backwards from possibilities that were heretofore discarded in the 'selective search' process. alas, the correct "patch" move/s may have already been found, but previously discarded as not strong or strong enough in its selective search process. in a game with finite although extremely large choice of moves, brute force calculation will always prove superior, but moves based on "feel" which is what a NN is attempting to do, can indeed find holes previously not seen by sheer calculation. and in fact, this is the very reason that machines, for chess at least are able defeat humans. in a game where 'feel' is the superior attribute, then humans would prove superior. which is why a good human driver will always be superior to a machine driver and im talking about everyday driving where unlimited possibilities of events can occur, NOT race car driving where events are large but still limited to going around an oval track with no traffic signs, human crossing, rain, snow, wind, etc. also a robot would prove superior as it is not subject to G force vectors as a human would be changing heart rate, blood pressure etc. similar to why even simple chess machines were better than beginner human chess players; they never 'hung' a piece, so just by not leaving pieces en' prise, would beat most beginners.

[@youuuuuuuuuuutube]

Had this game been played by humans, it would have been the greatest of all time.

[@darrenhughes5423]

This is why I'm subscribed great content great explanations keep it up 👍

[@kingscrusher]

Cheers, K

[@JauntyTeo]

What sorcery is this?! Great content btw

[@dickmacgurn590]

There are probably a thousand variations to this after the queen sac so no human will ever win using this line lol

[@INTJIsland]

When the traditional chess engines blew by the human players, it looked like they would simply be unchallenged as they got better and better. A few years ago I read a comment online where it was asserted that a NN could never beat a top chess engine. Now things are in flux once again. Alpha Zero shook things up, and then Leela came along, and NN chess engines are "the talk of the town." What will the future of non-biological intelligence bring us, not only in chess but in all areas of life? What a time to be alive! When I was in high school it was still slide rules for math and science because it would be years yet before handheld calculators would obsolete the slide rule. I seen so many revolutions that digital electronics have brought us that I have to shake my head. I maintained CAT scanners in 1981 and then in 2009 actually had to have a CAT scan run on myself. The amount of time for them to process 10 slices on me was significantly less than the time it took to do one scan in 1981. Things are getting faster and more powerful every day, and if Ray Kurzweil is at all correct the rate of improvement is exponential, and even more impressive, the rate of increase in the rate of improvement is exponential. We are still in the embryonic stage of A.I. and it is barely starting to crawl around on it hands and knees today. What it gets up on his feet and starts to run, it will be beyond belief. From pencil and paper and slide rules to all of this in one lifetime, now that is something to celebrate. My grand-kids will think that I truly lived in the dark ages. But what they won't realize is that the way things are today will seem even more like the Dark ages to their grandchildren because change is exploding. This is truly exciting! Thanks for sharing this game. You did a great job analyzing it. I wonder how long it will be before we humans will simply have nothing at all to gather from a game from these titans, because they will be so far above us that it will not make any sense at all? And one day they will say the same thing about how an A.I. will diagnose and treat patients. Why did the A.I. doctor do that? It makes no sense? "Who knows? But it cured the patient of a disease that would have been terminal a generation ago." That is the future, and it is coming at us at warp speed.

[@exelmans8855]

INTJ Island you have no idea what you talking about. Technology just make things worst.

[@INTJIsland]

@@exelmans8855 Have you considered your opinion at all? Aside from the fact that you are here and your comment would have been impossible to exist on this platform without technology, we would have an average life expectancy of around 25 or 30. We would still have universal slavery and starve to death when a bad winter came along. Technology has freed us from the animal existence, and the barbaric practices of the past and given us houses, heat and abundant food. Of course it has a downside, and it may one day consume us all. But it does not only make things worse. Surely you see this.

[@ThePavelkomin]

One of the best comments I've ever read on YT so far.

[@kdhavle]

Something I wrote nearly a year ago. kammusmusings.blogspot.com/2018/05/the-machines-are-coming.html

[@johnkarford6430]

Great comment. But in my opinion money rules the world and if A.I ever gets to a point of curing cancer of anything of that sort the money masters of the world will control it and use it to benifit them. Just like the pharmaceutical industry is controlled today. We're Just pawns.

[@seasideman]

Astonishing. It takes at least 20 and possibly 30 moves before that queen sac shows some real advantage for black. The slow improvement of position by Antifish over that period is exceptional. Thanks KC, your analysis helped me understand this mind-meltingly complicated game.

[@Bobby-fj8mk]

I enjoyed that. It's strange that both sides gave up castling rights. It's getting beyond human comprehension as we wouldn't normally do that. Every chess book tells you - "castle early"

[@michaeljamesmagallanes1346]

Bro, it's over exaggerating. Hehe

[@Bobby-fj8mk]

@ResistCom It's rare though - we usually castle.

[@commercialandresidentialpl7337]

Great game. I have been watching your videos for 5 years. You have helped me peak at 2128 lichess rating at 3min games. Thank You KC.

[@kingscrusher]

Cheers, K

[@SmithnWesson]

One advantage that stockfish has, is the ability to evaluate the search tree further down. The heuristic at the bottom of the tree it's not as good, but it still can get deeper. One relatively simple way of negating that advantage, is to remove pieces off the board. Fewer pieces, means that there is less to search, and hence less advantage when searching. If the anti engine can obtain early structural advantage, with pawn alignment or something similar, and then start taking pieces off the board, ultimately can end up with a better position. The goal of the anti engine, is to get to the end game, with a modest structural advantage, and without being destroyed first. I think if you built an anti engine, that is trained to play well both against traditional Leela, as well as Stockfish (in other words, alternate back and forth when you are training), it may end up toughest of all.

[@kingscrusher]

Great comment, K

[@5y89sdfih]

I think one of the reasons this sac works is the time it takes white to free up the h1 rook. Black gets to fully develop and start attacking while the white rook is stuck in the corner. In effect black traded queen for bishop, knight, and the reduced value of that rook. By the time it got free it was too late. This reminds me of how I've heard Kasparov talk about attacks and how he counts pieces (basically ignoring opponent pieces that are out of play and can't help defend). I know traditional engines try to account for trapped/restricted pieces but the neural nets seems to be more nuanced in how they evaluate them

[@jarirepo1172]

My thoughts exactly! Both sides development seemed a bit awkward first, but after black lost / sacrificed queen all black pieces became wonderful while whites pieces remained useless. White queen never had anything to attack, so black was free to solidify and expand advantages. Great game!

[@kingscrusher]

Great comment, K

[@SeattleMarc]

Would love to see more anti-fish games, the concept is fascinating.

[@WorldSeriesBound]

So, this is what it takes to save the French? 🤣

[@leaccordion]

Matthew Freeman Yes! Maybe it's a second French Revolution and the "Marie Antoinettes" need to get their heads sliced off once in a while.

[@balthazarbeutelwolf9097]

Antifish did not do so well in the final of CCC7 against Stockfish, Leela, and Leelenstein, ending up fourth. It had quite a few wins against Stockfish (the SF matches against Leela and Leelenstein were more drawish), but even more losses. Perhaps one of the problems is that SF development never stands still, so the weakness you are trying to exploit may have already disappeared in the next SF release, and that is the release you end up playing against.

[@dannygjk]

I smiled when I read your comment because a NN can be trained faster than chess software can be developed largely 'by hand'. NN's are the future check out some articles on the amazing progress of NN's in many fields not just games.

[@johnvuillemot4805]

@@dannygjk yeah, but they train off of problems that no longer exist and the whole data set is corrupted

[@-_Nuke_-]

"If the opponent is very good he will place his victim in an environment he can control, toss the dog a bone... find his weakness, give him just a little bit of what he thinks he wants and then the victim will gradually start to hang himself, consumed into his own assumptions... The victim does all the hard work, you are just helping along " Mr Green couldn't had said it better himself! Amazing game!

[@stephantaylor9599]

Thanks for another insightful look at neural network chess. Always informative, clarity pristine. In terms of the compensation that black got for the Queen here, I returned to the earlier comment you made, regarding the preference Stockfish generally has for the white side of the French. You indicated that one of the factors maybe because of the space advantage that white usually gets. In this game, the space advantage was all black, and it made a huge difference. When the added factor of the rather useless Rook on h1 is included, and topped off with the central control and passed pawn, it seems to me that black "saw" further, and was entirely dominant. This is fascinating. This kind of advantage is what Alphazero consistently got as white against the French and QI defences. So this really does help to point out holes in computer chess algorithms and evaluation functions, I think. Thank you again.

[@johnkarford6430]

That was insane. Can you imagine playing like this and beating a GM. On another note wonder why stock fish didn't just block the check and castle. His rook was completely useless

[@hazelelloyd]

KC, you hit on my pet use for NNs - diagnostics and assisting in the determination of where things can go wrong or right. You really understand the positive outcomes that NNs really have in this world. Good job!

[@kingscrusher]

Cheers, K

[@brianteskey2425]

This kind of brilliance would have been impossible with a book game. It’s a shame tcec does not realize they are missing out on brilliant games by NN. I’m pretty sure they want A/B engines to stay relavent as long as possible hence why all games are book. Book games are basically training wheels for sf

[@warrendsmith6832]

around 12:31, black could fork Q&R using Nc2. Apparently neither side is interested in/worried about that, which is another aspect of the general view of this game that normal material values are not a good guide. Black's Nb4 is excellent while the white Ra7 is not doing much.

[@kissarmin7130]

Nc2 doesn't work because of Qxa5+

[@warrendsmith6832]

@@kissarmin7130 Ah, you are correct. Stupid of me to miss that.

[@leaccordion]

Very thorough analysis kingcrusher. Written game analyses can be time consuming unlike your modern visual version. I visit other excellent chess sites and I admit yours is still #1 in my favourites.

[@kingscrusher]

Cheers, K

[@wateim3951]

combine anti-Stockfish with Stockfish move recognition and then make the general program make normal moves until it recognizes it's playing Stockfish, then switch modes. Quite possible and with the same general training setup (hardcoded) or even more generally, have both modes suggest moves simultaneously and weight the normal vs anti-stockfish solutions by the probability that it's Stockfish.

[@kingscrusher]

Great comment, K

[@warrendsmith6832]

Black's minors and rooks are like a swarm of ants, they just keep getting better while white's pieces including his queen never do much. Antifish somehow realized that was going to happen.

[@rogerrothman]

Thus might be the most astonishing game you’ve ever shown us!

[@kingscrusher]

Cheers, K

[@danielhouse6244]

Black Mirror is fantastic, and the episode that you're referring to is truly frightening.

[@kingscrusher]

Cheers, K

[@paulbloemen7256]

What a fantastic game! And it is kind of a game changer, at least to me: I thought Black's position after 19. ..., Kd7 looked hopelessly bad, where 20. Bc7 was the logical punishment, and Black could prepare himself for resigning. But there is a huge deceiving action going on, based on the ideas of the past that prove to be wrong. Software targetting the misconceptions of other software, that is hugely profitable I'm sure. That is, targetting mistakes beyond the horizon of whatever evaluation function: could this be of use for Leela itself too? To me, it is the fast lane for improvement, not relying on the self learning games where deceiving positions only may appear once in a while, but concentrating on mistakes you know were there for the taking. A very human approach, learning from mistakes, preferably one's own mistakes: it is like training on penalty kicks with football.

[@kingscrusher]

Great comment, K

[@AgentSmith911]

SF slowly being dismantled is not something that is considered an easy task. Hopefully this will help the SF developers to improve it so that the engine can evaluate positions at an even more accurate way in the future.

[@AySz88]

Awesome work on captions BTW :D

[@joseraulcapablanca8564]

A very interesting game and an interesting Project. i must say that i have transcribed and translated some of your videos., to Norwegian. Your English is idiosynctaic, but not difficult to understand or transcribe, thanks KC keep up the good work

[@SpaceCadet4Jesus]

What I learn from this.....is to give up my more valued pieces early, then when my astonished bemused and totally off guard opponent starts relaxing and smiling, to crush him with a unexpected pawn storm. I wonder how that will turn out...gulp.

[@davidchang8428]

That was amazing!

[@kingscrusher]

Cheers, K

[@sausage4mash]

most people playing this as white after the queen was trapped would ask themselves why is black continuing to play on? obviously, it's a different level of understanding, a level that's beyond my comprehension.

[@leaccordion]

Lord of the Pies - Ditto, mine also.

[@dbcane]

If you really think about it sure pieces have a set value but that only represents their value sitting on starting squares. If said piece is a monster on the board it's worth way more. In this game back got a monster bishop pair, a monster center pawn chain and killer uncontested knights. Add it all up and that's worth way more than a 10 point Queen sitting on your back row. Makes too much sense, we humans just fear playing in this manner so the ideas don't often show up on our radar. This Leela, alpha zero era has taught us something its to see clear and have no fear.... and calculate like a god.

[@kingscrusher]

Great comment, K

[@fburton8]

35... g4 Stockfish: "Mom! Mom!"

[@guepardiez]

I like the new manually revised subtitles. Thanks to AI, youtubers don't need to create them from scratch, and I imagine the revision doesn't take too long, either.

[@prem_tamilsiddha8987]

17:58 a second crazy queen sac 😎

[@kingscrusher]

Fun comment - Cheers, K

[@usamoronocracy526]

Great video !!! Did i miss the links to AntiFish and BetaOne or could you add these ?!?! Thx ;-)

[@TheAfroNoah]

wow, just wow

[@kingscrusher]

Cheers, K

[@niceguy100000]

Wow! Alien goodness again.

[@simpleman4215]

I relly enjoyed this game, like a lot. Where can I download the pgn?

[@kermitthefrog418]

Lol an engine designed just to beat stock fish? That’s when you know you’re the best I guess

[@dannygjk]

It's not that clear anymore. The antifish project was undertaken as an interesting fork from the Leela project. Leela btw is doing well vs SF 10, (yes ten).

[@kermitthefrog418]

U don’t see any1 making an anti-houdini

[@dannygjk]

@@kermitthefrog418 lol as I said, "The antifish project was undertaken as an interesting fork from the Leela project. Leela btw is doing well vs SF 10, (yes ten).

[@kyledekeyzer9439]

I cannot calculate this game anymore, ftw coming from a french. We should talk, even meet one Day great kingscrusher. Grtz Rfx- Alexandre F. 💙💚💛

[@pukulu]

stockfish definitely values its queen very highly. I suppose that it can get fooled once in awhile, when the queen can't find any targets.

[@kingscrusher]

Cool comment, K

[@paulbloemen7256]

The point system to value pieces is a human construction, a rule of thumb that works quite well, for us, humans. These AI-Zero machines don't care for any human constructions, they only value moves that maximize the chance to win the game. So, all kinds of surprises, to us, humans, are possible, showing us ways to win the game that seem completely unfeasible to us. This, to me, is the point of these AI-Zero machines, showing us what really matters.

[@stefanholbek2449]

Thanx, Mr. KC! For us deadly lower rated morons who enjoys the game - which these machines will NEVER learn! - there is some "fighting spirit" to be taken away from this game: You may NOT be that bad off with two pieces and a pawn for the Queen IF ... repeat: IF ... you have control in the center, diagonals for the Bishops, a weak or trapped King, passed pawns or otherwise some form of compensation. The big question or task is of course being able to evaluate this correctly whereas being material down leaves a depressing impression on the psychological side of things, which these machines obviously does not suffer from. But all in all: interesting times, we're living in!

[@douglasquaid7550]

intriguing

[@kingscrusher]

Cheers, K

[@vargas2022]

Spectacular.

[@kingscrusher]

Cheers, K

[@iliketurtles5180]

No pgn?

[@julioandresgomez3201]

The brand new neural network Allie is impressive too. It already won one game to Houdini. To Houdini! Last season Leela couldn´t win a single game neither to Stockfish nor to Komodo nor to Houdini at 90 minutes. Even this very season is still to do so.

[@kingscrusher]

Cheers, K

[@philipstevenson5166]

A chess boggart.

[@modolief]

4:52 - as I have mentioned before: Why?? You say this is a really good position for white.

[@schroederluck7984]

The white king is very safe while the black king is dancing around the middle of the board. The white pieces control more space and are more active. It's tough for black to develop and generate an attack because all the pieces are pushed back with the exception of the dark square bishop.

[@modolief]

Thanks 😀

[@RipperMatricus]

the less pieces on the board the more a queen becomes unstoppable... here we have just the opposite, all minor pieces still there and even a pawn up...>in this case the evaluation of a queen Q=10 is simply not there, far from... especially when opposites minor pieces work harmoniously well together and then that rook in the corner doing nothing... stockfish not so mighty after all this time

[@Idkwhattonamess]

W video

[@rahelagha7638]

Just tell me why you hate stockfish too much ?

[@landilevanaj3499]

Wow !!!!

[@kingscrusher]

Cheers, K

[@rahmahdirasuciprimalovita5119]

KC understands the psychology of chess better than Jerry

[@Jehoshophat]

Me nural net work is bester than that there computer and I crushes thems all tha time. That was a fantastic game .

[@kingscrusher]

Cheers, K

[@richardrussell5695]

The future is AI everything will be enhanced!