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Relevant tweets from Demis; Lee Sedol is playing brilliantly! #AlphaGo thought it was doing well, but got confused on move 87. We are in trouble no
by mikeyouse 11y ago
Relevant tweets from Demis;
Lee Sedol is playing brilliantly! #AlphaGo thought it
was doing well, but got confused on move 87. We
are in trouble now...
Mistake was on move 79, but #AlphaGo only came to
that realisation on around move 87
When I say 'thought' and 'realisation' I just mean the
output of #AlphaGo value net. It was around 70% at
move 79 and then dived on move 87
Lee Sedol wins game 4!!! Congratulations! He was
too good for us today and pressured #AlphaGo into
a mistake that it couldn’t recover from
From: https://twitter.com/demishassabis https://twitter.com/demishassabis
- comboy 11y agoI'll risk assumption that somebody from Deepmind team is reading this. Guys, please, publish charts of win prob estimated by alpha go in time during these games. Some heatmap telling which moves did it consider as best for both sides during the games would also be cool, but that's surely more time consuming to prepare. It would be great to be able to have such things for top pro tournaments in the future.
- magoghm 11y agoThat would be awesome.
- lifthrasiir 11y agoI.e. Something like [1] for every move. I was a bit disappointed to learn that such table is only available for that particluar move at the first reading. [1] http://www.nature.com/nature/journal/v529/n7587/fig_tab/nature16961_F5.html http://www.nature.com/nature/journal/v529/n7587/fig_tab/natu...
- fdej 11y agoOff-topic: we (the human species) have built an AI that can master the game of Go, but we don't yet have the intelligence to publish charts correctly on the web. That blur of a JPG is half a megabyte!
- cooper12 11y agoYeah honestly that would be much better presented as an SVG since its mostly solid colors and geometric shapes. Every browsers supports them, and all the big image editors as well; the trouble is that the rest of our software and culture hasn't caught on. Why am I taking bitmap screenshots of websites when they're almost completely text? We need to start building a tools ecosystem around vector graphics. An extra bonus would be a machine-readable representation of the board as well. We live in a digital age, but its almost like we're cavemen still dealing with the modern equivalent of analog formats. (And at least analog has fidelity)
- dr_zoidberg 11y agoScreenshots might not be the best example, since there may be some "shiny cute effects" going around. However, reading your idea sprang another one in my head: screenshots shouldn't be restrained to the same rendering resolution as the rest of the system/the screenshot resolution should be configurable. I don't require the screenshot to be instantaneous, I require it to appear instantaneous. In that sense, if the whole rendering pipeline is working to give me a framerate of 60 fps, then I could spend ten times as much rendering a screenshot without that delay being noticeable. Also, why on earth does Windows (don't know the behaviour on Linux/Mac) apply ClearType to a screenshot? That has always bugged me, there are some situations where you tolerate it and others where it hurts.
- massemphasis 11y agoIt didn't master anything. What the DeepMind team did was make an "AI" which means it can _imitate_ (to a certain degree) of "playing go".
- taejo 11y agoWhat's the difference between "imitating" playing go and playing go, when it can beat any one us at go?
- glasslion 11y agoActually, it's a tradition that both Players should replay the game after the match, discuss about good moves, bad moves and what they were thinking during the match. I felt so sorry for Lee Sedol when I saw him lose the second match, facing an empty chair ,and he could only ask one of his friend to review the game. https://zh.wikipedia.org/wiki/%E5%A4%8D%E7%9B%98 https://zh.wikipedia.org/wiki/%E5%A4%8D%E7%9B%98
- ktRolster 11y agoHe made $30k for losing that game, so I don't feel too sorry for him.
- vowelless 11y agoIf it really was about money, I don't think he would have spent so much of his life dedicated to Go ...
- simondedalus 11y agoyeah, not to belabor it, but if you can do something like be a champion in go or chess, chances are you have the mental skillset to do something exponentially more lucrative.
- _yosefk 11y agoI dunno, Bobby Fischer was kinda deranged, for instance, and that often hurts outcomes in otherwise "lucrative" positions. Incidentally, he is credited with raising chess player compensation through his demands. Generally I'd guess you're right though.
- iheartmemcache 11y agoMaybe not a leadership position but I've worked on the engineering side of quant work and am familiar enough with fairly advanced Go / Chess players (e.g. national youth champions for age brackets for the US) to know that most of them could make enough to retire off one years salary during the boom years of algorithmic trading (~2003-2007ish). I'm not sure how you define "deranged" (AFAIK, that's not a medically defined term within the DSM-IV) but most of those brilliant people end up being a little 'off'. My father was an academic, one of the people he went to graduate school with was working in Boston while I was a child. He was absolutely groundbreaking work but he's so difficult to collaborate with (think: the mannerisms of Richard Stallman) that he's been floating around universities until his welcome is worn out. He can figure out remarkable things in higher level computational chemistry, but he can't really figure out humans. Had he decided instead during the 80s to work at Renaissance instead of pursuing academic research, he almost certainly would be worth in the low hundreds of millions.
- techdragon 11y agoI wish some of these had been re-tweeted by the @DeepMindAI account. I'll definitely be keeping an eye on Demis' account during game 5.
- leereeves 11y agoAny chance of explaining the mistake on move 79 to someone who's only played a few casual games of Go?
- chillydawg 11y agoAlphaGo enlarged a group that was at risk of atari (loss to opponent) instead of correctly trying to divert attention to elsewhere on the board or starting a new fight or simply writing it off. If basically added stones to a group that was almost certainly dead and allowed the opponent to punish it heavily, thus giving away more stones than it had to.
- toolslive 11y ago"Do not anthropomorphise computers. They really hate that" (NN)
- zsiciarz 11y agoBy NN you mean a neural network, of course? That makes even more sense...
- toolslive 11y agoNN = nomen nescio ("I don't know the name") You use it when you cannot name the source of a quote, or when you would like to protect the source. https://en.wikipedia.org/wiki/Nomen_nescio https://en.wikipedia.org/wiki/Nomen_nescio
- zanalyzer 11y ago... wrote the bot trying to hide its identity
- andrepd 11y agoWouldn't "-Unknown" convey the same sense without the possible confusion?
- haswell 11y agoI think this conveys a slightly different meaning. When I see "-Unknown", I interpret it as "somebody said it, but no one is quite sure who". "(NN)" in the current thread was used to indicate "I personally don't know", which does not imply the quote is unattributable.
- simonebrunozzi 11y agoNN is (was) also used in neapolitan comedy, derived from earlier use throughout the Roman Empire and Middle Age. The "figlio di NN", or "son of NN" means someone who was found and adopted (typically by nuns) and whose parents were unknown. NN can be used in general for people whose origin is uncertain. I think in this specific case it's a bit misleading - although the wikipedia article seems to suggest that NN can also be used as a synonym for "unknown", although from a historical perspective it is a bit incorrect. The literal translation from Latin creates some confusion if you didn't know the context. I hope this helps.
- denim_chicken 11y agoIt feels really weird to see someone being showered with congratulations for beating a computer program. What exactly is he being congratulated for? For probably triggering and then capitalizing on a bug in AlphaGo's AI? For showing that human resolve, perseverance and a "fighting spirit" can trump a flawed AI, at least until the AI gets fixed? For giving DeepMind extremely valuable test data that will only accelerate the refinement of AlphaGo's AI? For helping to advance an amoral field of study that can potentially delegitimize everything that currently makes humans unique and extraordinary?
- grumpy-buffalo 11y agoHow about just for playing a good game of Go?
- deleted 11y ago[deleted]
- denim_chicken 11y agoSo I suppose the fact that the opponent is a computer program should not be factored into the reaction to Sedol's win at all. I hope your reductionist explanation is not accurate because it would imply that we are already so highly conditioned to machines and to AI that this match is thought to be no different from a match between two humans.
- ethanbond 11y agoThe machine beat him 3 times and was more or less expected to win again. It didn't, which would imply that Sedol played an exceptionally good game. Seems pretty obvious to me.
- jdmichal 11y agoYou're acting like following arbitrary sets of rules to maximize a value function isn't something that computers excel at. The only thing that was holding up computers for Go was simply time; there were too many possibilities to consider. Humans are really, really good at heuristically trimming possibilities, but sometimes to the detriment of finding maxima.
- zouhair 11y agoHow frigging smart Sedol is?
- Tempest1981 11y agoKind of cool to know you're as smart as algorithms that require 1920 CPUs and 280 GPUs
- avar 11y agoThey've said it doesn't require that, AlphaGo running on a single machine beats the cluster they're using 25% of the time.
- sltkr 11y agoSo based on current data, Lee Sedol is exactly as good AlphaGo running on a single machine.
- lettergram 11y agoEven on a single machine it has the "memory" of virtually any Go game AlphaGo could be fed.
- Houshalter 11y agoProbably better. If we assume a uniform distribution across possible win rates of Sedol vs AlphaGo, then update it with bayes rule, we get 33% chance that Sedol will win the next match. That's not factoring in other information, like Sedol now being familiar with alphaGo's strategies and improving his own strategies against it. So there is a good chance he is now evenly matched with AlphaGo, and likely much better than the single machine version.
- emcq 11y agoDoubtful; I don't think comparing such small W/L distributions will be illustrative. On the other hand, the Nature paper shows the single 8 GPU machine performs similar to the 64 GPU cluster, but the larger clusters perform a comfortable margin better. [0] By a single machine winning many games relative to the distributed version, really it's just saying that the value/policy network is more important than the monte carlo tree search. The main difference is the number of tree search evaluations you can do; it doesn't seem like they have a more sophisticated model in the parallel version. The figure suggests that there are systematic mistakes that the single 8 GPU machine makes compared to the distributed 280 GPU machine, but MCTS can smooth some of the individual mistakes over a bit. [0] http://www.milesbrundage.com/uploads/2/1/6/8/21681226/8771727_orig.png http://www.milesbrundage.com/uploads/2/1/6/8/21681226/877172...
- karussell 11y agoJust in case someone wants the commentary around this move 78 https://www.youtube.com/watch?v=yCALyQRN3hw&t=11413 https://www.youtube.com/watch?v=yCALyQRN3hw&t=11413
- panic 11y agoHere's the Myungwan Kim commentary around that same move: https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h33m https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h33m. He had been looking with Hajin Lee at variations involving the move beforehand (https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h28m1s https://www.youtube.com/watch?v=SMqjGNqfU6I&t=1h28m1s), so he immediately noticed that AlphaGo made a possible error in its response.
- thomasahle 11y agoBut Kim also jumped a bit backwards and forward for a few moves, until he finally decided it was a mistake. It didn't seem 100% clear.
- kerkeslager 11y agoProfessionals are understandably hesitant to call AlphaGo's plays mistakes after the first few games, because AlphaGo had played a few moves that seemed like obvious mistakes (the eyestealing tesuji under the avalanche and the fifth line shoulder hit) but later proved to be very strong moves. Remember that when go is your career, your reputation is based partly on your ability to analyze games accurately, so calling a move a mistake and finding out later that it was strong would be a big embarrassment.
- deleted 11y ago[deleted]
- SilasX 11y agoOT: What's with using monotype for quotes? That's breaks line wrapping and makes it hard to read on mobile or small screens. I don't get why people do it.
- jkyle 11y agoLooks good in desktop browsers.
- hguant 11y agoIt's also customary when quoting large sections of text. I'm not sure if this carried over from email, or from academic texts (where if your quote is more than a line or two, it needs to be formatted differently).
- nightpool 11y agonot really: http://i.imgur.com/uxqERat.png http://i.imgur.com/uxqERat.png (you have to be very careful about what indentation level you're at, how long your lines are, etc, etc, things that people just don't do most of the time)
- mst 11y agoI think mostly people forget that > works and that therefore you can do > q
- mst 11y agoI think mostly people forget that > works and that therefore you can do > q
- mst 11y agoI think mostly people forget that > works and that therefore you can do > quotes like this since it's markdown - often you get commentish things that allow limited HTML plus indented code blocks, and people get used to using the latter as the only thing that works everywhere
- ScottBurson 11y ago
- nopinsight 11y agoNot so coincidentally, "This was when things got weird. From 87 to 101 AlphaGo made a series of very bad moves." [1] The bad moves in the eyes of humans could be risky bets or the horizon effect. [1] [2] AlphaGo's use of deep neural nets (value networks) to evaluate board positions should significantly help counter the horizon effect, but since move 78 by Lee Sedol which turned the situation around was unexpected by some top pros (Gu Li referred to it as the 'hand of god' [1]), the patterns which follow are likely rare in possible game states and therefore not strongly embedded into the value networks, leading to AlphaGo's loss. I hope the DeepMind team will help enlighten us on this in the near future. [1] https://gogameguru.com/lee-sedol-defeats-alphago-masterful-comeback-game-4/ https://gogameguru.com/lee-sedol-defeats-alphago-masterful-c... [2] https://en.m.wikipedia.org/wiki/Horizon_effect https://en.m.wikipedia.org/wiki/Horizon_effect
- hibikir 11y ago78 was hard, but not impossible: If you watch the AGA commentary of the game, they had two pros at the time 78 happened, and they found 78 as the best answer a few minutes before Lee did, expecting AlphaGo to go with a stronger, yet still good not good enough 79, that left the game even, instead of basically lost. Then they were elated about how AlphaGo seemed to have failed to read the whole thing, and instead of doing preparatory moves for a nasty ko fight, the best option at the time, AlphaGo just took a route that provided almost no compensation. If anything, it seems to me that AlphaGo's problem here might be the time management: Seeing a really scary situation, Lee Seido just sank many minutes into reading the problem, going pretty much all the way to byoyomi time. A human, after seeing something like that, would figure out that their assessment of the situation and their opponent's is very different, and spend a lot of budget trying to figure out what was wrong. AlphaGo just didn't see the problem, and didn't just budgets its time to analyze the position to death. It moved slower than before, but not really that much, and ended up making moves a kyu player could see as terrible. Either way, I'd love to see Deepmind giving us all a good postmortem of the 70-100 range of moves.
- karmakaze 11y agoI concur that better time management may have made a difference. Beyond that, I think that AlphaGo may still be missing a type of component. From the descriptions of it, the policy network generates possible moves from board positions, and the value network evaluates the probability of desirable outcomes. How this is different than human play is that strategic assessment and planning are implicit in the middle layers rather than a 'conscious' element to searching and decision making. I'm not saying that this is a necessary component as AlphaGo has already done exceptionally well. I do believe this kind of 'middle-out' processing producing and evaluating strategic concepts could make it better handle unusual circumstances. Being trained on high amateur and pro games, it will best respond to the most conventional of those types of games, more unconventional the game becomes, the worse it would fare in terms of efficiency of move generation and choices of which to evaluate.