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This was probably the closest game in the series. Livestream: https://www.youtube.com/watch?v=mzpW10DPHeQ https://www.youtube.com/watch?v=mzpW10DPHeQ A few mon

• wheresmypasswd 11y ago
  > What this underscores, if anything, is the accelerating pace of technological growth, for better or for worse. While growth may be accelerating, this is simply the result of one big paradigm shift in deep learning/NNs. Once we've learned to milk it for all its worth, we'll have to wait for the next epiphany.
  • hmate9 11y ago
    Milking neural networks out completely is pretty much AI as depicted in the movies. If we can milk it completely there probably isn't a need for the next epiphany.
    • swombat 11y ago
      Or, at the very least, the next epiphany need not be human-designed. Just train a neural network in the art of creating AI paradigms and implementations that can do general purpose AI. Once that's "milked", the era of human technological evolution is finished.
      • foota 11y ago
        That sounds like a bad idea.
        • swombat 11y ago
          It's the core idea of AI, the primary reason why it is suspected that developing strong AI will inevitably lead to the end of the human era of evolution.
        • deleted 11y ago
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      • YeGoblynQueenne 11y ago
        I don't want to be mean, but that's like saying you'll train a magic neural net with the mystical flavour of unicorn tears and then the era of making rainbows out of them will be finished. Or something. I mean, come on- "the art of creating AI paradigms"? What is that even? You're going to find data on this, where, and train on it, how, exactly? Sorry to take this out on you but the level of hand-waving and magical thinking is reaching critical mass lately, and it's starting to obscure the significance of the AlphaGo achievement. Edit: not to mention, the crazy hype surrounding ANNs in the popular press (not least because it's the subject of SF stories, like someone notes above) risks killing nascent ideas and technologies that may well have the potential to be the next big breakthrough. If we end up to the point where everyone thinks all our AI problems are solved, if we just throw a few more neural layers to them, then we're in trouble. Hint: because they're not.
        • swombat 11y ago
          I totally see your point and my purpose is definitely not to be alarmist and sound the alarm that skynet is about to come out of AlphaGo or some other equivalent neural net. But I think the opposite attitude is also false. As others have pointed out, we don't really know how the brain works. Neural nets represent one of our best attempts to model brains. Whether or not it's good enough to create real intelligence is completely unknown. Maybe it is, maybe it's not. Intelligence appears to be an emergent property and we don't know the circumstances under which it emerges. It could come out of a neural network. Or maybe it could not. The only way we'll find out is by trying to make it happen. Taking a position that neural networks cannot ever result in strong AI is as blind as taking a position that they must. This is Hacker News, not a mass newspaper, so I think we can take the more nuanced and complex view here.
    • _yosefk 11y ago
      You're basically saying that there's no task (including passing the Turing test, programming web apps, etc.) which requires intelligence and is best tackled with either something else than a neural network or with NN combined with something else. I think it's a pretty bold statement which is really hard to back up by anything but a hunch.
      • deleted 11y ago
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      • swombat 11y ago
        Our current assertion is that neural networks basically replicate the brain's function, so our current understanding of this paradigm is that "milking neural networks" is going to match or exceed human general purpose intelligence. I believe hmate9 is correct. If this paradigm is exploited to the full, unless we've missed something fundamental about how the brain works, we don't need to bother ourselves with inventing the next paradigm (of which there will no doubt be many), because one of the results of the current paradigm will be either an AGI (Artificial General Intelligence) that runs faster and better than human intelligence, or, more likely, an ASI (Artificial Super Intelligence). Either of those is more capable than we are for the purpose of inventing the next paradigm.
        • argonaut 11y ago
          No deep learning researcher believes neural networks "basically replicate" the brain's function. Neural nets do a ton of things brains don't do (nobody believes the brain is doing stochastic gradient descent on a million data points in mini-batches). Brains also do a billion things that neural nets don't do. I've never even taken a neuroscience class, and I can think of the following: synaptic gaps, neurotransmitters, the concept of time, theta oscillations, all or nothing action potentials, Schwann cells. You have missed something fundamental about how the brain works. Namely, neuroscientists don't really know how it works. Neuroscientists do not fully understand how neurons in our brain learn. According to Andrew Ng (https://www.quora.com/What-does-Andrew-Ng-think-about-Deep-Learning https://www.quora.com/What-does-Andrew-Ng-think-about-Deep-L...): "Because we fundamentally don't know how the brain works, attempts to blindly replicate what little we know in a computer also has not resulted in particularly useful AI systems. Instead, the most effective deep learning work today has made its progress by drawing from CS and engineering principles and at most a touch of biological inspiration, rather than try to blindly copy biology. Concretely, if you hear someone say "The brain does X. My system also does X. Thus we're on a path to building the brain," my advice is to run away!"
  • HaikuEU 11y ago
    Could you care to explain what was that big paradigm shift ?
    • bla2 11y ago
      This four-part series explains it well: http://www.andreykurenkov.com/writing/a-brief-history-of-neural-nets-and-deep-learning/ http://www.andreykurenkov.com/writing/a-brief-history-of-neu...
  • JulianMorrison 11y ago
    But that's what technological growth is. A series of epiphanies, building on what came before.
    • msbarnett 11y ago
      Yes, but an epiphany is not evidence of an accelerating rate of epiphanies, nor evidence that such epiphanies will continue apace into the future.
      • JulianMorrison 11y ago
        You can look at the past for that, although obviously it doesn't predict the future. But it ought to be a priori obvious, at least, that the more you know (as a species), the more surface area of knowledge you have to synthesize into an extending step beyond the known.
        • ska 11y ago
          You could look at the past, but that isn't what the claim did. In fact looking at the rate of change in applications over an "epiphany" period is probably the least useful estimate of progress & rate of change in progress.
• seanwilson 11y ago
  > In game four, we saw Lee Sedol make a brilliant play, and AlphaGo make a critical mistake (typical of monte carlo-trained algorithms) following it. Can you explain why this is typical? What can be done against this to strengthen the algorithm?
  • rymate1234 11y ago
    I can't remember where I read this, but one theory was that the move Lee Sedol made was thought to be unlikely by AlphaGo, and so didn't explore down that path. When Lee Sedol made the move, the AI was in unknown territory as it hadn't explored down that avenue.
    • seanwilson 11y ago
      > When Lee Sedol made the move, the AI was in unknown territory as it hadn't explored down that avenue. Sounds similar to what a human would do then: you wouldn't spend much time simulating in your head what would happen if your opponent made a very atypical move or a move that would seem very bad at first thought.
      • kqr 11y ago
        That's exactly it. The difference, as far as I have understood it, is that there was a similar move that is typical, but in that particular situation, pretty simple reasoning (of the highly abstract "if this then that so this must lead to that" sense) leads a human to conclude that this version of the move is superior. So while atypical in the sense of "occurring infrequently", it was not a difficult move to find for a player of that level – all the pro commentators saw it pretty much right away. This might be the one weakness of AlphaGo, which is interesting.
    • dfan 11y ago
      David Silver said at the beginning of the broadcast of game 5 that AlphaGo's policy network had given Lee Sedol's move 78 only a 1 in 10,000 chance of occurring.
  • 11y ago
• aquadrop 11y ago
  > There's no doubt that with further refinement, we'll soon see AI play Go at a level well beyond human Will we though? AlphaGo trains on human games, so can it go well beyond that level? Will it train on its own games?
  • krig 11y ago
    It is already mainly training by playing against itself: https://googleblog.blogspot.se/2016/01/alphago-machine-learning-game-go.html https://googleblog.blogspot.se/2016/01/alphago-machine-learn... > To do this, AlphaGo learned to discover new strategies for itself, by playing thousands of games between its neural networks, and adjusting the connections using a trial-and-error process known as reinforcement learning.
    • aquadrop 11y ago
      It's still based on human games. It plays itself but the way it plays was inherited from human. I wonder if there is some fundamental barrier to what you can reach with reinforcement depending on your base.
      • relic 11y ago
        It is based on human games until it can explore well enough to sufficiently break away from local optimums.
      • aflinik 11y ago
        Having it learn on human games was just a way of speeding up the initialization process before running reinforcement learning, it didn't limit the state tree that was being searched later on.
  • deleted 11y ago
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  • StreamBright 11y ago
    It already went beyond human level, look for Go players commenting on the game, citing that they would have never thought about steps that the AI made. In a sense it brought new strategies to the table that humans can learn and apply in human vs human games.
• cgearhart 11y ago
  >A few months back, the expert consensus was that we were many years away from an AI playing Go at the 9-dan level. These kinds of predictions are almost always useless. You can always find people who say it'll take n years before x happens, but no one can predict which approaches will work, and how much improvement they'll confer. > What this underscores, if anything, is the accelerating pace of technological growth, for better or for worse. What? This is a non-sequitur. Continued advancement doesn't mean that it is accelerating, and even if this does represent an unexpected achievement that doesn't mean that future development will maintain that pace. Appreciate it for what it is - an historic achievement for AI & ML - and stop trying to attach broader significance to it.
  • lefnire 11y ago
    You sound like the kinda person who says "AI will never drive," "AI will never play Go." True there's a lot of hype, which ML experts are concerned may lead to another burst & winter. On the flip-side there's a lot of curmudgeonly nay-sayers such as yourself at which ML experts roll their eyes and forge ahead. What I find is both extremes don't understand ML, they're just repeating their peers. ML is big, and it's gonna do big things. Not "only Go", not "take over the world"; somewhere in between.
    • cgearhart 11y ago
      I'm actually very optimistic about the state of AI and ML lately. The difference is that I don't anthropomorphize the machines or ascribe human values to their behavior. I absolutely believe AI will drive (and save lives); I have always believed that AI will play Go; I believe that AI will grow to match and surpass humans in many things we assume that only humans can do. Humans aren't perfect, but that doesn't mean that machines who outperform us are perfect either. AlphaGo plays Go. It probably doesn't play Go like a human (because a human probably can't do what it does), but that's OK because it also appears to be better than humans. AlphaGo is interesting not because it has done something impossible, but because it has proven possible a few novel ideas that could find other interesting applications, and adds another notch to the belt of a few other tried and tested techniques.
  • 11y ago
• NotUsingLinux 11y ago
  this reads as the professional go world couldn't wait for this (Alphago) to arrive to find new ways of play new moves.
• gambler 11y ago
  There's no doubt that with further refinement, we'll soon see AI play Go at a level well beyond human No doubt? Seriously? What kind of knowledge do you have to make such statements? There are plenty of examples where technology has rapidly advanced to some remarkable level, but then almost completely plateaued. For example, space travel or Tesla's work on applications of electromagnetism. Heck, even other areas of AI research. I really don't see why people here readily assume that this particular approach to computers playing Go is easily improvable. Neither do I see why everyone assumes there will be no discoveries of anti-AI strategies that will work well against it. With neural networks involved, it's hard to say. And all we have so far is information about about, what, 15 games? Some of which were won by people. Mind you, those people never played AlphaGo before, while the bot benefited from a myriad of training samples, as well as from Go expertise of some of its creators. I'm also tired of all the statements about "accelerating progress". It's not like all the AI research of the past was useless until DNNs came along. That's the narrative I often get from the media, but it misrepresents the history of the field. There was no shortage of working ML/AI algorithms in the past decades. The main problem was always at applying them to real-world things in useful ways. And in that sense, AlphaGo isn't much different from Deep Blue. One big shift in the field is that these days a lot of AI research is done by corporations rather than universities. Corporations are much better at selling whatever they do as "useful", which isn't such a good thing in the long run. We're redefining progress as we go and moving goalposts for every new development.
  • tim333 11y ago
    Well, little doubt. When did any technology suddenly stop improving when it reached human levels?
  • YeGoblynQueenne 11y ago
    >> Corporations are much better at selling whatever they do as "useful", which isn't such a good thing in the long run. Yep. There's a grave risk that funding to AI research ends up being slashed just as badly as in the last AI winter, if people start thinking that Google has eaten AI researchers' lunch with its networks and there's no point in trying anything else. Incidentally, Google would be the first to pay the price of that, since they rely on a steady stream of PhDs to do the real research for them but now I'm just being mean. The point is, we overhype the goose that lays the golden eggs, we run out of eggs.
• mcv 11y ago
  > There's no doubt that with further refinement, we'll soon see AI play Go at a level well beyond human Why is there no doubt? I strongly doubt there even exists a go level that's well beyond human. There is hypothetical perfect play of course, but there is absolutely no way to guarantee perfect play. And while I have no way to judge, I've heard that 9p players may not be all that far removed from perfect play. One legendary player once boasted that if he had black (no komi, I assume), he would beat God (who of course plays perfect go). There is of course no way to know if that's true or gross overconfidence, but it's certainly possible that there's not all that much room left beyond the level of 9p players. AlphaGo will no doubt improve, and reduce the number of slips like his move 79 in the 4th game, but it's never going to be perfect, and there's always the chance that it will miss an unexpected threat.
  • baddox 11y ago
    You could always argue what "a level well beyond humans" means, but I'd say if a computer can consistently dominate the best human players that would count.
  • TwoBit 11y ago
    Given the crushing that AlphaGo did, I don't believe your statement about humans having near perfect play.
    • goldbrick 11y ago
      Can you quantify "crushing"?
      • eru 11y ago
        4 - 1.
    • mcv 11y ago
      Not all humans, obviously, but 9p players really are far, far better than other players. And there's another 9p who has won 8 out of 10 matches against Lee Sedol, so there's nothing superhuman about a 4-1 result at that level. I'm really just objecting to the description of this as "beyond human". Yes, it's good, and it's many orders of magnitude beyond my level, but so are Lee Sedol and other 9p players.
• ChuckMcM 11y ago
  In an odd way, it makes me more optimistic about fusion power plants in my lifetime. The reality is that we work on these advances but are terrible at predicting when we will achieve them, and then one day we find we have arrived. That AlphaGo can play at this level suggests that similar techniques could help other parts of the infrastructure (like air traffic control) and that would also positively impact the quality of life for a many air passengers every year.
  • eru 11y ago
    Fusion power is neat, but not really necessary. Fusion would have similar political problems to fission; and the economics aren't much improved either. Perhaps if we ever ran out of fissionable material, fusion would become economic.
    • lyle_nel 11y ago
      What political problems might that be?
      • eru 11y ago
        All the anti-nucular protestors? Or eg whatever made Angela Merkel turn off the German reactors after a reactor of a very different design in a very different set of circumstances in Japan broke. Fusion is just yet another nuclear reactor design as far as politics might be concerned.
        • lyle_nel 11y ago
          Ah is see. Although I would not put it past people to protest nuclear fusion, it would be strange indeed, since nuclear fusion does not produce the same kind of radioactive waste(shorter half-life) as alternative nuclear technologies.
• colllectorof 11y ago
  A few months back, the expert consensus was that we were many years away from an AI playing Go at the 9-dan level. Any sources for this statement? I've seen it repeated over and over again, but without any specific examples of who those experts were or what they said.