Google Deep Mind AI Alpha Zero Devours Stockfish

[@stalkingwolfchess7972]

Right after Stockfish wins the computer championship, AlphaZero shows up "Oh hai guys, whats this game called? Chess?", 4 hours later he is like "Here stockfish, munch on these 2 pawns and get in your corner like a good boy"

[@dannygjk]

I can't click like because it is at 64.

[@ZenMasterScr3wy]

Like that scene from the Matrix... "I know Kung- Fu!"

[@Cscuile]

Just FYI, a bunch of people, including GM Nakamura, and myself believe Stockfish had an unfair handicap. Not to mention, SF was running on a older, weaker engine without a book. Just be aware of that.

[@zlac]

Alpha Zero also had no book and it only "trained" for 4 hours. They will most likely train Alpha Zero much more (perhaps many months) and then do official chess competition against all the strongest engines.

[@mogyorospusztai]

the 4 hour is also a lie, it was training for at least twice as much longer + it didn't only play without an opening book, it had no access to tablebases either

[@elfakyn]

This is incredible... pieces hanging everywhere that can't be captured because of complicated tactics. This is definitely a game that no human would play.

[@chronicmasterbaiter5467]

Arya Well tal played couple of games like that

[@juliansoto2651]

The difference is that most of Tal amazing moves has hidden mistakes. Stockfish would destroy Tal tactics because of its deep understanding of complex positions.

[@postmasterpez]

The scary thing is that they would, only 100 times worse.

[@lucgagnon7169]

Tal was the best !!

[@chronicmasterbaiter5467]

Julián Soto I was not questioning or saying that tal is on same level as alpha zero. I ONLY said that it's "like" that in the way that it has pieces hanging everywhere that can't be captured

[@dineshssairam]

11:44 "Stockfish resigned the game." Google should use that phrase to market AlphaZero.

[@berksezer4751]

Not many people would understand that though - unfortunately -.

[@johnrubensaragi4125]

*cough* leela chess zero *cough*

[@jangtheconqueror]

AlphaZero is not for market, yet.

[@chriscurtain1816]

I don't think Google have any say in the matter. Alpha Zero will be putting Google up for sale soon.

[@johnwest6690]

I've never seen an engine resign before

[@ryvanlorenz9299]

*Me: Moves E4 DeepMind: mate in 33*

[@toluwalogoyomi-momoh1968]

😂😂😂😂😂

[@atree9284]

I like to imagine this as DeepMind being another player who looks like Ben Shapiro, whispering this under their breath after you play.

[@isawicameiconqueredandcame3708]

Don't overestimate yourself. Before the game: +/= You: 1. e4?? Alpha: Mate in 4

[@zakariyamohamed6388]

Lol

[@sparksfly4421]

u'd get mate in like 7 bruh

[@Brandon-a-writer]

I imagine Deep Mind with Hal 9000's voice. "I'm up the exchange, Dave. You will lose the endgame."

[@agadmator]

+Brandon Nobles :D So far, I imagined a woman's voice, but Hal works :D

[@stephen0793]

Haha!

[@Lavalle.mp3]

>Stockfish wins a piece >Deep mind:"This game is too important for me to allow you to jeopardize it" >Proceeds to crush him anyway

[@criskity]

"Mate in 73. You lose".

[@Fukashima1]

"I think you missed it, Dave"

[@iLikeMiIfs]

Magnus Carlsen: "I often sacrifice a pawn to get a better position" DeepMind: "singular?"

[@michaelmonitor7443]

ahhhh smite 1v1 legend king

[@GlobalWarmingSkeptic]

"Get me out of this corner!" "I'm sorry Stockfish, I'm afraid I can't let you do that"

[@NaoshikuuAnimations]

Take a look at your history. Everything you built leads up to me.

[@zytlib6758]

@@NaoshikuuAnimations lMAO

[@coleschemistrychannel4172]

Naoshikuu So fucking underrated

[@1abi07]

erbh

[@ichbin1984]

"I'll beat your ass in chess and jeopardy..."

[@elfakyn]

This whole game is as if Deep Mind just decided where it wanted its pieces and Stockfish was powerless to stop it.

[@ryuisonline8816]

Arya it's like being able to solve a rubik's cube without an algorithm

[@MrSupernova111]

Just like my games with me as Stockfish in this scenario. hahaha

[@kasparov937]

Great way to put it, yeah truly out of this world chess

[@bruceli9094]

A0 combines the best human strategies + cold hard calculation of a computer + it's own unique insights. It's PERFECTION.

[@TheNokkius]

actually if I understood it correctly it's just cold hard calculation of a computer + it's own unique insights

[@a.nyangao.m]

maybe i am an idiot but the most fascinating part was the opening. in 4 hours it practically had come up with a classical main line of the queen's indian. in a weird way validating human effort of decades haha, but that is scary in it self, thinking that ok now we know we did well, because this algorithm knew it in 4 hours.

[@ryuisonline8816]

Νυανγκάο Athanasios Makris But just think, the only reason the computer was able to come up with these solutions was because humans created it. It might be a lot better at chess than any human being, but it shows that humans have that capability to improve.

[@a.nyangao.m]

I can't argue with that. We can certainly improve. And I won't act like I know how these algorithms work, but Aga said that it was given nothing but the rules. So I took that as it played d4 because it quickly figured out that controlling the center is important for example and then built up from that. But maybe the true culprit is the opponent, Stockfish, that knows the openings. A0 was finding the best moves to continue from what Stockfish was fishing for in its database. So we still have done well in chess as a species haha

[@womplestilskin]

It knows all the openings now, btw. And wins all of them too, the PDF is pretty short, take a look.

[@a.nyangao.m]

womplestilskin Thanks, I will

[@dogfish2988]

I think this 4-hours thing is a bit delusory ... it probably played more games of chess against itself then ever played by humans in the history of mankind or some crazy stuff.

[@Ceber911]

Maurice Ashley: stockfish any comments on the game? I mean you were making some not smooth moves against Deepmind. How do you feel? Stockfish: I mean what do you want me to do?!?

[@agadmator]

+Cameron Smith Nice :)

[@zanetruesdale8336]

I laughed pretty hard at this.

[@MrSupernova111]

Loving the Maurice Ashley's comments. Hahaha

[@DarkestValar]

haha epic comment

[@limitedinfinity5095]

Cameron Smith ahahaha

[@maulanatriharjuno7584]

2:11 agadmator: deep mind made stocfish like a little... me: bitch agadmator: kid me: kid

[@agadmator]

+Maulana Harjuno :D

[@abhiavirneni2842]

😂

[@lovelight5337]

:🤣

[@KagirinaiYonaka]

😂

[@electricmaster23]

Be honest-you were going to say 'bitch' but censored yourself, didn't you? :D

[@misternoodle1236]

When I woke up this morning, the last thing I expected to see was Stockfish being completely roflstomped into oblivion.

[@ottiscool6612]

You still haven't

[@Garroxta]

You could have told me that N. Korea launched a nuke onto China and it would have shocked me less than this news. Chess is just the beginning. Soon AI like this will use human-like intuition to replace our doctors and lawyers and even inventors. I can't wait.

[@dannygjk]

Ottis...wake up, it's over.

[@Pintkonan]

roflcopt0r

[@chriscj9007]

@@Garroxta What if it replaces humans itself? Scary

[@harsh3608]

It is interesting that Google's deep mind does not just calculate moves but also has a plan of steering the games into positions to immobilise the pieces no matter what it takes and then bust open positions by sacrificing some material to gain advantage(kinda like Ivanchuk) but maybe this is the greatest strategy possible in chess and what stockfish has done so far is to just calculate by brute force without any strategy

[@bruceli9094]

Exactly, A0 combines the best human strategies + perfect calculation of the best engines + it's own unique insights.

[@paultan5419]

Deep mind also uses brute force.....

[@firstnamelastname7298]

@@paultan5419 yes but it does immobilize the enemies pieces which is very advanced

[@paultan5419]

@@firstnamelastname7298 The AI has no idea what chess is or strategy it's using. It's merely a naive algorithm using a trained machine learning technoque to evaluate all the possible states (with pruning) and pick the best move. It has no idea what chess is, or any concept of what it's doing at all.

[@paultan5419]

@@firstnamelastname7298 my point is that whatever techniques it uses, no matter how advanced, it's still brute force (from a computer science perspective )

[@bruceli9094]

Stockfish = Usain Bolt AlphaZero = Jet Engine

[@arkadiuszjandylewski152]

No no no! It is Jiren vs Goku!

[@jaystock9202]

Stockfish = hamster AlphaZero = Lamborghini

[@lred1383]

It's more like: Whoever the best human chess player is: Usain Bolt Stockfish: Ferrari Deepmind a0: F-22

[@nxtgameroxs1268]

Too weak, too slow.

[@jonaskoelker]

Like shooting stockfish in a barrel.

[@duckgoduckgo]

this is gold

[@FiikusMaximus]

@@duckgoduckgo this is finegold

[@nabisco0523]

Agad, all I gotta say is, when you reach 100k, 200k, 300k, and so on, don't ever change the way you operate this channel! You're simply the best KZbinr I've ever watched, since KZbin started in 2006 or whatever. It's okay to tweak things here and there to try new approaches, but the very basic premise of your channel is hands down the best on the internet. Thank you for bringing so much joy and laughs to my life man! I been subbed to you since 5k, from an old channel I used.

[@agadmator]

+BayToTheVeg Thank you for such wonderful words. I'm not planning on changing it, maybe I'll fit in a vlog here and there :)

[@joesotham]

I agree!

[@kurthamming7718]

Which is fair enough since we all don't (want to) pay for this content!!

[@Buranazi]

More like one of the worst chess channels. I guess beginners like this kind of rambling without any explanations

[@nabisco0523]

Buranazi that's not very nice! If it annoys you so much, don't watch or comment silly :)

[@TigerDuDe77]

Can we have more Deep Mind games please?

[@AlexisPerez-yy7dk]

2:12 "deepmind makes stock fish look like a little...b..kid"

[@kenl.3298]

😂😂😂

[@time7260]

Damn I thought I was the only one

[@shashishekhar----]

I laughed so hard at this.

[@Amethyst_Friend]

What this game shows me, is that human opening theory is too conservative. Deep Mind used its knight aggressively and early, to tie Stockfish in knots and achieve a decisive advantage. Of course, you have got to be be damn strong to get away with this!

[@Ceber911]

Learning It Quietly well also humans wouldn’t play the way stockfish would IN REACTION to Deep Mind’s moves.

[@HawkOfGP]

The problem is that some of the lines these engines may play are so risky that if you aren't 100% of accurate you will blunder the whole game and even the greatest GMs will struggle to find those moves every time.

[@plutogaming6495]

agad you said stockfish was rated around 2400 in the beginning of the video, isnt it 3400?

[@agadmator]

Yes, it is :) I meant 3400 :)

[@therealsachin]

Looking at the way game went ... we so understand why you said 2400. Scary! 😳

[@sohansubrat4669]

Hello agadmetor,nice video. By the way can chess openings be mastered without knowing theory? If no, what about chess 960 ? All that is required is creativity.

[@AshishTiwari-mz7yl]

agadmator's Chess Channel ya right..because when ever i make stockfish and magnus carlsen app play....stockfish crush him...so it can't be 2400

[@martinmannapsoo762]

The gams lasted for 7 seconds

[@bass2564]

Deep Mind is the name of the Google company that developed the software, AlphaZero is the name of the program.

[@mikes.8647]

There was probably a mistake regarding the ratings; I think stockfish is 3300+ and not 2300+ :)

[@agadmator]

+mike s. Yes, I meant 3300 :)

[@sabjekill]

Also, they played 100 games of which Deep Mind won 28 games and 72 draws were made. The supercomputer they used to train it takes 4 hours, but that would take around 70+ years on a regular PC, so the question is, when will it be as light as other engines out there, and when can it be used for training humans?

[@elfakyn]

Look at how Deep Mind and Stockfish only push the minimum number of pawns necessary... This is very interesting and educational

[@jp2kk2]

Arya once you push a pawn, you cant un-push it.

[@elfakyn]

Alan M. In human play you can see pawns marching forward in order to anticipate a good piece placement or to protect a well-placed piece. But Deep Mind just tossed his pieces in the enemy's camp with little to no support.

[@Djorgal]

Not only in the enemy camp, he puts his pieces straight under attack. I mean, I tend not to put my bishops in the diagonal of a pawn.

[@teddymills1]

I love pushing pawns. I think I gain tempo and space. Usually they get too far ahead and cannot be protected. Divides the army. Checks with no purpose.

[@GinoTheSinner]

I watch these games and sometimes zone out for a second or two, then I get taken back by stockfish somehow being in even deeper trouble than just some 4 moves earlier. I continually have to pause the video and go back to look how it happened. There are some very seamless transitions from position to position and stockfish is fumbling in the dark. This is incredible.

[@grolich]

Amazing. Just a note of the variation shown where Stockfish didn't capture on g5 - actually Stockfish considers it a very bad position for black to capture, and the reason is clear - The variation you gave contains a small error - instead of the incorrect hxg7 in the middle of the variation (which indeed leads to a balanced position according to Stockfish), just Qd4 leads to a winning position for white. Amazing game :) Thanks for posting

[@alankilgore1132]

Thanks for making this game available, it is the first I heard of it. It appears that 100 games were played between Stockfish 8 (S8) and the Google entry, AlphaZero or DeepMind (DM). It seems we are comparing apples/oranges in terms of the hardware on which the games were played. DM was played using 4 TPUs (Tensor Processing Units which are little super-computers that do specialized work). S8 was said to run using 64 threads (does this imply CPUs?), and 1G of hash. S8 isn’t the most recent version, and it also plays endgames better when it has Syzygy endgame tablebases available. The paper doesn’t mention this. It does say that S8 was searching at 70 million positions per second, which is about right if 64 CPU’s are available. DM searches 80 thousand (that’s right) positions a second and according to the paper, is highly selective in its search. This has been the holy grail of chess engines since they were first conceived. Humans don’t look at every possible move, but how do you design software to think like humans. S8 and other modern beyond-human (they use superhuman way too much in the paper) engines do it by pruning the hell out of the search tree. All captures and some checks are examined, but after that, only a few “quiet” moves qualify for examination. This is how S8 can search so far ahead in a short amount of time. We also don't know either side had an opening book, though I’m guessing no. I agree with your Tal comparison. DM does appear to always be looking for the series of attacking moves. Very aggressive. But here we must consider a couple of things. Tactical move sequences, where both sides are trading pieces can only be resolved by tree searches using current state of the art engines. Has the AI of DM found a better way? After all, it is only searching 80K positions/second. Is this enough speed to resolve deep combinations? They paper doesn’t describe what goes on in their searching, but we know from experience that most chess games are won/loss by the balance of material. This is especially true at the early stages of the game, where if you are down a minor piece, it is a tough battle to catch up. Searching a tree and only considering the captures can be fast, since the problem self-reduces by the nature of removing a piece from the board with each capture. The paper doesn’t indicate how “deep” their search is. I’m sure more will come out of this as more papers are published. The claim was made that DM was only given the rules of the game, which I assume means it was not given information about the merit of various elements, such as is having a Bishop pair vs a Knight pair is good or bad, but it might have been told to consider that feature in its learning. This is how chess engine evaluations work. they measure many "features" of a position and then come up with a number that represents how good/bad the position is. Regression analysis is usually used to combine many features. Again, not sure how Google did it with DM, but I’m curious. Their algorithms must measure something, so what are their features? AI techniques have been around for some time, and there is nothing new about self-learning chess engines. I would take some claims, such as it only was taught the rules of chess, with a grain of salt until we know more about what the neural network is measuring. Show me the details! Back to the game and the pivotal moment. 21. Bg5 WOW! I agree, where did this come from? I let SF chew on this for 90min looking at the top 5 moves and it got up to 41 plies (20 moves by each side) and found Bg5 as the best move. SF is only searching 1.3 million positions/second on my slow laptop, but according to the paper, each side was only given 1 min per move. So, based on some simple math, SF should have found Bg5 in 90 min on my laptop if the move was that decisive. I then had SF search the top 5 moves... So what this really means is, DM found a 20 move ahead move and SF8 agrees. well beyond what we mere humans can figure out! You ask what DM’s rating is? Based on the paper, it is just slightly better than SF8 at 3300-3400. They played 100 games, with each side playing white and black equally. DM won 25 games as white and rest were draws. DM won 3 games as black, the rest were draws. DM did not lose a game. Amazing….

[@1001011011010]

Alan Kilgore I don't think DM was given any openings, and I don't think they are that close if DM never lost once in a hundred games but won many games, with the rest ties. I could be wrong about the opening books though

[@klieu90210]

The way AlphaGo was developed, I completely trust that DeepMind was given nothing but the rules. It is amazing what trial and error can achieve without anything to prejudice your perspective on how a game ought to be played.

[@1001011011010]

lsduuhyik ygytyuui 1i thought they just played 100 games.

[@graysonparker1593]

There are videos on how deepmind works, or how the newest one which uses reinforcement works. Reinforcement learning basically means it plays against itself over and over again, recognizing new patterns over and over again that lead to a win more often. It starts just playing randomly at first, and recognizes patterns that lead to winning( like castleing). The thing that is amazing about this is that there is no human involvement whatsoever. It has learned from complete scratch, and has deduced the best possible lines and theories and ways to play the game in 4 HOURS. This is also kind of sad as well. If you run deepmind longer, it will eventually get to a point where it is playing chess the best way it can possibly be played. If they do that, chess will literally be complete, in my opinion. There will be no further discussions about what the best move is in a position. Sure, you don’t have to play that move, but the fact that you know it is the best is kind of sad to me.

[@1001011011010]

Grayson Parker this is an assumption. Perhaps let it play against itself even longer and it will realize that last move previously thought best was actually not. Even though it was only 4 hours, do you know how many thousands or millions of games it went through?

[@monkeysrightpaw]

Very moving. NEVER thought I'd see something hand stockfish such a profound loss. Damn! What can I say.

[@cubesandpi]

I know you probably don't want to do 2 games from this set, but example game 9 is a crazy game that I would love to see you review. 1. d4 e6 2. e4 d5 3. Nc3 Nf6 4. e5 Nfd7 5. f4 c5 6. Nf3 cxd4 7. Nb5 Bb4+ 8. Bd2 Bc5 9. b4 Be7 10.Nbxd4 Nc6 11. c3 a5 12. b5 Nxd4 13. cxd4 Nb6 14. a4 Nc4 15. Bd3 Nxd2 16. Kxd2 Bd7 17. Ke3 b618. g4 h5 19. Qg1 hxg4 20. Qxg4 Bf8 21. h4 Qe7 22. Rhc1 g6 23. Rc2 Kd8 24. Rac1 Qe8 25. Rc7 Rc826. Rxc8+ Bxc8 27. Rc6 Bb7 28. Rc2 Kd7 29. Ng5 Be7 30. Bxg6 Bxg5 31. Qxg5 fxg6 32. f5 Rg8 33.Qh6 Qf7 34. f6 Kd8 35. Kd2 Kd7 36. Rc1 Kd8 37. Qe3 Qf8 38. Qc3 Qb4 39. Qxb4 axb4 40. Rg1 b341. Kc3 Bc8 42. Kxb3 Bd7 43. Kb4 Be8 44. Ra1 Kc7 45. a5 Bd7 46. axb6+ Kxb6 47. Ra6+ Kb7 48.Kc5 Rd8 49. Ra2 Rc8+ 50. Kd6 Be8 51. Ke7 g5 52. hxg5 1-0

[@agadmator]

+CubesAndPi I will probably do 1 more, checking all of them now

[@iNeedPhone]

3 wins, 47 draws with Stockfish on white. 25 wins, 25 draws with AlphaZero on white.

[@1001011011010]

Démian Janssen that's crazy

[@jtmv8915]

Oy that bishop sac...

[@philippdrescher6012]

@@iNeedPhone That shows how strong the starting position actually is for godly players. 😂

[@nathanjxaxson]

Wow. Deep Mind *obliterated* Stockfish. I have never seen Stockfish get so utterly *demolished*. Unreal.

[@oscarrulez007]

Nathan Xaxson o

[@simonfido4278]

When I play against strong Engines my Position always looks likes Stockfishs in this game. Scary

[@verycurlyo]

and deep mind plays french defence....agamator sheds a tear

[@GodleyBeast]

Lmao

[@keedt]

re the slow conversion: another thing to consider is that alphazero works by optimizing the winning probability (unlike stockfish which optimizes the evaluation in centipawns), so it happily chooses a slower conversion if this means that it's more sure to win. Also in the Go version, conversions were often strange to the human eye

[@tobiastrust4232]

This is so beautiful! Stockfish plays like a engine BUT Deep Mind plays like a Human who is 10 times stronger than the strongest human! Crazy and also shows the scarry future of AI's

[@yaseen157]

In the middle of watching this game and I just want to say, in reference to your survey earlier, this is the length of video I am most content with on this channel - you give enough information on each move and it's direct implications, and you should keep up the great work. Now back to watching, and I'm thoroughly enjoying this game so far

[@blamtasticful]

I love how you self-censored at 2:14 lol ;)

[@00tact]

blamtasticful. I missed that 😂😂

[@miscelanea5351]

AMAZING! I was studying Reinforcement Learning, (which is the same framework from which Deep Mind's AI was trained) when I saw this video. At the end I just got back the enthusiasm I was loosing for the lack of sleep. Amazing time to be alive! Reinforcement Learning/ Machine Learning / Deep Learning is starting to make a great technological revolution. What a time to be alive!

[@villaholland]

2:11 deepmind makes stockfish look like a little... U wanted to say Bitch haha😂 I feel you it pronounces smoothly.

[@agadmator]

+Robb V. Of course not :D

[@VictorUdd]

I thought he was about to say a little boy but changed it to kid. I don't think it is that common to use slang such as "little bitch" if you're not from the states.

[@villaholland]

Victor Udd-Peterson i aint from the states

[@stateofdecay2210]

it is still worth watching even after almost 2 years , thanks for sharing the most beautiful end game in the history of chess

[@TheMuffinBagare]

I've recently seen an AI similar to this called OpenAI. It learns exactly like you've described Deep Mind - by continuously playing against itself given only a rule set. Now, OpenAI has been used in Dota2, a computer game, so it's quite different in that regard, but still very similar. And yeah, it usually beats the professional players very easily. In the case of Dota2 and many other video games, the games themselves are too complex to make a successful equivalent of Stockfish, but this new method seems very potent. If people tell the program what to do, it will only make "people-moves" so to say. If it learns by itself, however, it will make up new things, and people can in turn learn new ways of playing and exploiting things in the games from the AI. Very exciting to me! :)

[@milliern]

I think one comment you made is extremely insightful, and it is something I thought as I was looking at the endgame: when a strong human player is up the exchange in the endgame, it doesn't take long to finish matters off; and this is due to a collection of inaccuracies by your opponent. What this endgame shows is how much technical prowess is required in an endgame when no glaring inaccuracies are being made. Study the endgame, folks.

[@christianwtf2960]

I am working on my masters in mechine learning and I can tell you we are very far from skynet level ai. We are talking like probably not even my life time kind of time. Then again technology is growing at exponential rate so we will see.

[@whateverybodyknowswebuiltt3785]

Agadmator you analysis has really really emproved the longer you have done this

[@VideoNOLA]

Stockfish: "Your move, D." Deep Mind:

[@LightningSe7en]

Sends "sometimes to win a war, sacrifices must be made" to a whole new level. 2 pawns for 2 pieces that are not in play.

[@dineshssairam]

6:33 Deepmind to Stockfish: "Look at me! I'm the boss now."

[@michelevalenti85]

Great that you posted the arxiv article! Very professional of you, thanks :)

[@voidzminer1017]

Me looking at the thumbnail: THATS CALLED THE WOODEN SHIELD

[@omniversosindios7953]

This are the things that I love to hear about science and technology. Just incredible!

[@beev]

'This could be the greatest end game ever played in the history of chess!' - you nailed it with that line. Everyone. Mark this day. A paradigm shift in the application of AI in chess (and beyond)....

[@TioRubens1]

Hi agadmator, in the article you shared with us there are 10 games played between these two AI. The article is really good and I recommend people to read it

[@amirfarisazizi2082]

117 moves, unbelievable

[@bardhanjoy]

Symphony. This game is so beautiful that it has the same effect of a masterfully composed symphony which leaves it's audience speechless. I am deeply moved by this game.

[@FreethinkingSecularist]

Dude...you are the top youtuber on this particular AI subject!!!

[@MyWoodbeGood]

I love how chess is such an interesting measure for these things

[@htmlman1]

I'd be interested in seeing some of the self-play games that occurred near the end of A0's training. How do you beat something like A0? Only A0 knows.

[@mikes.8647]

I can't even describe how amazed I am; I mean, self-teaching for 4 hours and it destroys the strongest engine? o_O Thanks for this mister!

[@fujiapple9675]

3:48 "I mean . . . this is Stockfish." lol

[@samche11]

This just highlights the amazingness of a fact that human actually managed to pull a victory against Deep Mind in Go. Go is just so much more intangible and complex than Chess is..yet so much simpler at its core. A true Beautiful Game.

[@oslier3633]

What do you need to win a chess match? Alpha Zero: 3 pawns ad a knight.

[@jamesfleming1155]

I saw in someone else’s comment you said you might throw in vlogs at some point. I think that would be cool. Congrats on your channels success. Definitely my favorite chess channel!

[@otaku-chan4888]

I must be the only one here who doesn't know anything about chess other than how the pieces move lol To me, the guy reciting the letter and number coordinates immediately after a piece moves was unreal XD

[@hey8174]

Seems the best way to play is to accurately sacrifice your pawns for a positional advantage.

[@JMS1089]

This is frightening.

[@notexactlypaul]

Given that neural networks can be trained and theoretically produce different results, unlike traditional chess engines which are purely computational and bounded by the information fed to them, I wonder if we could identify some distinct "styles" that emerge from many iterations of Deep Mind. What if we trained 10,000 of these and found one which was more "tactical" and one which was "positional"? What if they played each other? What would happen if we fed the rules of the game into Deep Mind, but started with a set position? GMs are already pretty adept at arriving a set position 15-20 moves into a game, so having the best chess "entity" in the world play out moves from one of those set positions as a next level of preparation does not seem too far off in the future.

[@russelllomando8460]

Just setup your channel on ROKU. AWSOME!!!!

[@agadmator]

Cool. Let me know how it works :)

[@peterdao7346]

Alpha zero is actually called Alpha GO zero, it originally was designed to play a more complex game with exponentially more end game variations. They have used this same algorithm for so many different games, from PC to GO to chess now. That’s the most amazing part, and it’s gotten so good it doesn’t use human input (which is good, humans are bias and make errors.) so saying this, chess was probably a breeze, see that it was created to tackle harder issues, this is only the beginning for google and deepmind.

[@RobGcraft]

“I often sacrifice a pawn” Deepmind: “Singular or multiple?” “What” “What”

[@helloitismetomato]

Everyone talking about how impressive it is it taught itself to play at this level in only 4 hours, but remember that's 4 hours of running on Google's astonishingly large supercomputer cluster! It's still super impressive of course but since we're talking about chess computers, mentioning the processing power involved is important. There were actually two different models used: one that used 4 hours, another that used 9 hours of training. The 9 hour version won a 100 game tournament against Stockfish 8 at 28-0-72. It's worth saying there's good reason to think Stockfish would've been much stronger had it not been handicapped though - they used an old version and fixed move time to 1 minute, instead of allowing Stockfish to do its own time management which probably had quite a big difference on its strength. It's still important research and there's no question AlphaZero was stronger, but the research conditions were still a bit dubious.

[@crazyim5]

Someone has gotta say it: Skynet!

[@markevans7244]

That end game reminded me of the scene in The Matrix when Neo is blocking Smiths punches with one hand.

[@KavasPVP]

Mr. Anderson

[@AshishTiwari-mz7yl]

Wow..what a match...im very happy to see stockfish lossing a game as i play against it and he crush me like hell ..so it feels nice....😉 Hey agadmator when i saw that game of bobby fisher in which he player evans gambit(if i wrote it right) from that day im in love with that Openning...but as usual i can't play it that good...so can you show us a video fully analysing that openning or can you tell me a book to refer for mastering in it..??

[@aaronalfer2615]

I was hoping for Stockfish to win. So were most of the chess programmers who have spent some considerable time of their lives learning and developing conventional algorithms. It was a bit sad to see some AI from Google come out of nowhere and defeat the strongest chess engine. But we have to accept it, move on, and learn new methods. Although it's too early to conclude anything. More testing must be made: different hardware, different time controls, etc. Stockfish did not have an opening book! It's important. And also, I don't see many people mention that most of the games were DRAWN. Agadmator gives the impression that Stockfish lost all of the games. It's misleading.

[@aaronalfer2615]

pahom, so you are a programmer and you claim that Alpha0 is not AI? How is it not AI then? I'm genuinely curious. Because to me it totally seems like AI implementing unsupervised learning. I'm not familiar with details of Alpha0's implementation but we can all agree that the core of it is machine learning which is a field of AI. And even if the gathered data is then interpreted as evaluation it doesn't really matter, that's not the point.

[@aaronalfer2615]

pahom, I see, so you're a smart-ass. Good to know. Many competent developers worldwide use the term AI and they're completely fine with it. I'm not pretending to be an expert here: AI is not my field. But this doesn't suddenly make me not a programmer. I work with .NET platform, if you're curious. You can go and convince someone else in your superior intelligence. I'm not interested.

[@AshishTiwari-mz7yl]

pahom so you are saying that they are misleading us............ and how you know all this???

[@MalcolmBlk]

pahom AI stands for Artificial Intelligence. This term means a program that can teach itself to do something really good from a basic level without human input. Think about it as you would about a human mind: you teach your child, say, the basic chess rules, and after that you give him a chess set and tell him he has some time to play against himself and improve. This is what they mean by "intelligence". If it's "artificial", them it's a human made program that can teach itself. Google's Alfa Zero can teach itself to play chess, just like a human with real intelligence can, only way faster (like 1000 times faster). It also has more computing power for complex calculations of course, just like humans have a brain for that. That's why Alpha Zero is indeed an AI. It is not the final step of AI development by any means of course, but denying it is an AI is strange, as you know that it managed to teach itself, so what is the problem? If you were expecting AIs to be able to teach themselves to play chess without any inputs like basic chess rules, then your expectations may need to be altered, as no real world entity can operate with magic.

[@stateofdecay2210]

it is maybe the best ending game in the history of chess but this is indeed the best commentary about alpha zero in the whole Universe , thanks I think I watched this tenth times and it is still magnificent and has a lot of magic into it. and I also have an idea and I am going to do the exact moves against stockfish 8 and see what will happen :)

[@carlos-enriquetafuregido8642]

It's amazing but here is a comment of a machine learning expert (Pedro Domingos): "AlphaGo Zero is great, but hold on: self-play is one of the oldest ideas in ML, and humans take far less than 5 million games to master Go."

[@nielsliljedahlchristensen4924]

Here is a comment from a machine learning guy who is probably not as much of an expert as this guy you're talking about: AlphaGo Zero is so much stronger than any human could ever hope to be. If that's what it takes to "master Go", then it would take a human infinitely more games to master Go, because a human would never reach that level.

[@shadearca]

Yeah, but it is also a few thousand times better than any human who has mastered Go.

[@bleach123abc]

you can't possibly master go.

[@Lucalaurin]

I think it's very important to keep in mind how difficult it is for a software to play Go on a professional level. They only achieved that last year with alpha go (was it last year or two years ago?) before that there was no engine that could beat a top level go player not even the lower ranks of professionals. Agadmator brushes over this a bit but I don't blame him, most chess players don't know anything about Go.

[@KrishanBhattacharya]

The actual name of the engine is AlphaGo Zero. Deep Mind is the company that created it.

[@gJonii]

Krishan Bhattacharya it's AlphaZero. Alphago Zero is a separate engine that only plays go. Deepmind even had AlphaZero play against Alphago Zero, and win.

[@sulamy1955]

2:10 “Deep Mind makes Stockfish look like a little b- uhhh kid” We all know what you wanted to say...

[@Requinix17]

5:52 that image of stockfish with two knights, a bishop, rook and pawns all crammed into the corner completely useless, while the king in the opposite corner with the defending pieces getting overwhelmed...

[@EliteJovenAgent]

Nah deep mind would lose to beth’s queen gambit

[@raveendrank.n.3449]

Subconscious mind vs Alpha zero

[@boomerzilean]

3:47 stockfish? More like stuckfish

[@ForeignGuyMike]

AlphaZero's play style is pretty savage. It seems less concerned with just beating you and more concerned with forcing you to commit suicide.

[@batatapao3611]

I played a move AlphaZero played, 1.d4

[@fujiapple9675]

At 3:03 some engines recommend 10. Na6, developing the other knight to an inferior square to c6, but then one wonders about the future of the light square bishop.

[@GerHanssen]

Not a word about go, agmator. I am disappointed. But your surprised reactions are just like the ones in the go community, when they were confronted with AlphaGo: "This is beauty! Wow."

[@agadmator]

+Ger Hanssen I never tried GO. Don't think I would contribute much. Is there a good online server to tryout go? I am planning to learn the basics some time soon and maybe do a short video on it

[@GerHanssen]

Ah, that would be interesting. I am willing to help in one way or another. What I wanted to say is that this whole development of AlphaZero came out of the challenge to play go, and that would have been worth mentioning. I don't play online go very much. Pros nowadays prefer Tygem (www.tygembaduk.com/ehowto/tygemgo.asp), but there are at least 10 other ones, some of them 100% Asian. I know that from the videos of Haylee (kzbin.info/www/bejne/jHPZaIumnqqMapY). She is a top pro that played as a strong amateur commenting during the game while thinking. She picked the idea up from a chess player. She never mentioned who. Sensei's library (senseis.xmp.net/?About) tells you just about anything about go and the go community.

[@joesimon2018]

After watching a few of these Alpha Zero vs. Stockfish games I see a pattern in that: 1. Alpha Zero has less problems taking material losses in the early stages of game than Stockfish, which uses material evaluation more in assessing the position. In this way, Stockfish is more human in its approach to the game. 2. Alpha Zero gives equal importance to the concept of improving its position as it does at paralysing it's opponent from being able to improve its position. Every move seems to ask the question not only how it attacks or defends better....but how it limits the opponent's options to improve. Again less human. But of course these options are available to computers because their risk of making a mistake are far less. They have free reign in their ability to gamble because they never make simple,mistakes.

[@tellahsage6477]

Not having problems sacrificing material is less human? If anything, it's completely the other way around. Computers tend to be extremely materialistic when it comes to chess playing, it's why if you put most gambit openings into an engine like stockfish it'll say right away that you are worse but most humans have very few problems at all playing these positions

[@Ale_ssandro]

Ehm, Deep Mind developers? Hi. Just wanna say... if you see a woman with a shotgun, a very big man and a child, just run.

[@Phenom98]

Hasta la vista, baby.

[@muneebi8273]

HahahHa

[@kylecoleman4221]

Something interesting to think about is that in when alpha zero plays go it'll play some moves that are kind of slack and not as strong when it thinks it is far far ahead of it's opponent and there is minimal chance of it losing, this becomes very noticeable in alphas end game or when it played against humans. I don't know that much about chess but it'd be interesting I think to take a look at some of it's moves in the end or mid game from this perspective.

[@florin.lupascu]

The key aspect here is the 1 minute / move time control, as due to neural networks and search algorithms AlphaZero is far superior to Stockfish: 80k vs 70k evaluation speed (positions/second) in favor of AlphaZero! It would be interesting to see a 100 games match in standard time controls between these two... I would bet then the evaluation speed won't count as much and the result would be way more close than today!!! :)

[@mmalahe]

According to the paper, AlphaZero evaluates 80 thousand positions per second, while Stockfish evaluates 70 million per second, so in fact AlphaZero is vastly superior in terms of efficiency in the number of positions evaluated. However, each of those evaluations comes at a much higher computational cost.

[@hudsonmackay4206]

In some of the papers I have read, they have stated that the time control arguably places a greater handicap on alpha zero and that stockfish is stronger on quicker time controls

[@nielsliljedahlchristensen4924]

Neural network evaluating is really slow compared to the evaluation function of Stockfish. The 70k you mention is actually 70 million, but it's always nice to try and confuse people by pretending you know something when you really know nothing

[@vigneshiyer123]

From what i understand x it was restricted to 1 move per 1 minute compulsory and lot of things favourable for deep mind.. so we need to check it in a normal clock time

[@Zywl]

sometimes I wonder why spend years learning about a game that an algorithm can master in just 4 hours?

[@acezaro7927]

Because, in the end, it's still the humans who have the creativity to do those things, it was human intelligence that created AI, even though AI is vaaaaaastly superior in speed processing and effeciency, we still have creativity and a lot to be expected from :D

[@gamespotlive3673]

This game is so cerebral like no human understood the deep aspects going on between these two machines.

[@quivalla]

The next Chess engine to come out will play e4 and you lose instantly.

[@techpriestsalok8119]

Deepmind plays like it thinks the board is too cluttered with all its pieces. It gets rid of them but opens up the board so much in the process that stock fish is just stuck.

[@arsenalfanrichi]

I don't know if it is just me being a paranoid person, but This Alpha Zero has got me pretty worried, tbh

[@dickersonforever]

Alpha Zero took in to consideration run the world but at the end it seems prety point less for him, you know he calcula tes very far away and well at the end It's not interested

[@alienrenders]

I dunno. Seems like Alpha Zero also knows about the c6 weakness if you can't get d5. In fact, as soon as black's knight moved out of the way, white's knight moved into d6. It really doesn't want black to move that d pawn. You mentioned white's knight on d6 was attacking the bishop. I disagree. It doesn't care one iota about that bishop. It's there to stop any d pawn push. And as you mentioned, the black bishop move completely locks in the black knight and rook. The second time the black knight moves away from d6, white immediately attacks the black queen and proceeds to attack the king side until the White queen now finds itself on d6 again stopping the d7 pawn. The white queen stays there a long time seemingly tempting stockfish to try and dislodge it. And once black pushes the c pawn, down goes the other black rook. edit: It looks like Stockfish also knows about d5. d5 is what Stockfish would do on move 11 no matter the setting. It NEVER considers Bf6. The only move Stockfish considers is d5 here. This game looks manipulated to me.

[@FloydMaxwell]

These two players need to study more openings

[@FloydMaxwell]

For example, at 3:02, why didn't white take the dark square black bishop?

[@ryuisonline8816]

Floyd Maxwell that would just give up a powerful knight and allow black to develop their queen

[@FloydMaxwell]

Aren't bishops worth more than knights, and the dark square bishop the more valuable of the two?

[@verycurlyo]

Mate, they are beyond studying petty human openings

[@GermansEagle]

human opening cant even compare to these, it's on another level

[@florin.lupascu]

So, the version they used to play with is Stockfish 8: „To evaluate performance in chess, we used Stockfish version 8 (official Linux release) as a baseline program, using 64 CPU threads and a hash size of 1GB.” - page 15 in the pdf

[@manyqualms4747]

I can mate deep mind from this end position in 11 1/2 moves...😠

[@Lucalaurin]

deep mind wanted to humiliate stockfish by taking all the pawns first and then having it give up

[@stephen0793]

This makes Kasparov’s new book on AI and how we shouldn’t fear it even more current and pertinent- but I’m definitely more afraid now!

[@Todestuete]

I think we should definetely fear it, but that doesn't mean we should reject it. Not only could it be abused in the wrong hands, it might also get out of control. AI savety is a very important research topic.

[@galactica1419]

When I play stockfish, 30 moves in My pieces: my time has come

[@jellewever1225]

I had to setup the board and go threw analysis with Stockfish to see why f5 on move 20 for black does not work. It seems taking the Knight would not help after Qh4. And after fxe4 Bxe4 the Queen would need to drop back to h8, haha! Sorry if you covered this in your video, did not watch it till the end yet.