After Go, the next AI challenge they're looking at is Starcraft: https://twitter.com/deeplearning4j/status/706541229543071745
If that's true...they really just hate the Koreans LOL
AlphaGo beats the world champion Lee Sedol in first of five matches
451–460 of 596 posts
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#452This is my generation's Gary Kasparov vs. Deep Blue. In many ways, it is more significant. Several top commentators were saying how AlphaGo has improved noticeably since October. AlphaGo's victory tonight marks the moment that go is no longer a human dominated contest. It was a very exciting game, incredible level of play. I really enjoyed watching it live with the expert commentary. I recommend the AGA youtube chann…
Yep, terrific commentary by Myungwan Kim 9p on the AGA channel. For the folks who aren't as familiar with the game, how did you find the commentary (for any channel)? What would you be interested in hearing for events like these?
I really enjoyed Myungwan's down-and-dirty commentary, and watching him get lost in some variations, and it was just incredibly exciting to see him get won over to AlphaGo during the game. From about move 50, I was just viscerally excited to see where things went, and the game did not disappoint in any way.
I've read a few different reviews and watched Michael Redmond's live commentary as well, who obviously has a slower Japanese style of play than Myungwan, and his variations all exhibited a very thorough style and sensibility, but I think he missed the key moment, and Myungwan called it -- the bottom right just killed Lee Sedol, and it was totally unexpected.
And, Sedol was thinking about it too, because right after he resigned, he wanted to clear out that bottom right corner and rework some variations. I presume that's one frustration playing with a computer -- they'll have to instrument AlphaGo to do a little kibbitzing and talking after a game. That would be just awesome.
If you are very, very inspired by AlphaGo's side of this, it's really incredible to imagine, just for a moment, that building that white wall down to the right was in preparation for the white bottom right corner variation. The outcome of that corner play was to just massively destroy black territory, on a very painful scale, and it made perfect use of the white wall in place from much earlier in the game.
If AlphaGo was in fact aiming at those variations while the wall was being built, I would think at a fundamental level, Go professionals are in the position that chess grandmasters were ten years ago -- acknowledging they will never see as deeply as a computerized opponent. It's both incredibly exciting, and a blow to an admirable and very unusual group of worldwide game masters.
I loved every minute!!
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#453Earlier quoted context omitted.
1202 CPUs and 176 GPUs is the figure mentioned in the Nature paper. But it's important to understand that this is the computer used to train the networks used by the algorithm. It took about 30+ days worth of wallclock to train it. That's about 110 megawatt-hours (MWh) worth of energy required! During the play, the computational requirements are vastly less (but I don't know the figures). It's still probably more tha…
If your 110MWh to train is accurate, and the 25W used by the human brain reported in this thread is as well. This is equivalent to one person expending 500 years solely to learn Go.
The cumulative amount of person-hours that went into training Lee Sedol (All the hours spent training his instructors, sparring partners, developing Go theory, playing out, and drawing inferrences from the outcomes of long-dead expert players) is probably more then 500 years. AlphaGo, on the other hand, had to start from scratch.
Given the rules, and a big book containing every professional go game ever played, and no other instruction, it's not entirely clear to me that Lee Sedol would be able to reach his current skill level in 500 years.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#454Earlier quoted context omitted.
If it's any consolation, there are still tons of things humans are far better at than machines.
The only remaining are language-related. Natural languages are the next focal point of AI research.
Not true, humans are better than computers at Starcraft, even despite AI's tremendous APM advantage.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#455Earlier quoted context omitted.
What kind of source do you want? It's a saying in the go community, people believed (including me) that a bot couldn't beat a human in our lifetime, some people had more extreme view and thought that it would never be possible.
Anything written. I'll be particularly happy with higher "quality" sources -- books, quotations in newspapers, etc. -- but honestly, I'm not that picky and will accept an anonymous comment on a random forum.
"Fotland, an early computer Go innovator, also worked as chief engineer of Hewlett Packard’s PA-RISC processor in the 70s, and tested the system with his Go program. “There’s some kind of mental leap that has to happen to get you past that block, and the programs ran into the same issue. The issue is being able to look at the whole board, not the just the local fights.”
Fotland and others tried to figure out how to modify their programs to integrate full-board searches. They met with some limited success, but by 2004, progress stalled again, and available options seemed exhausted. Increased processing power was moot. To run searches even one move deeper would require an impossibly fast machine. The most difficult game looked as if it couldn’t be won."
http://www.wired.com/2014/05/the-world-of-computer-go/
The article then goes on to discuss how Monte Carlo was the real breakthrough.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#456Earlier quoted context omitted.
In case you're not aware, AlphaGo's key component is based on the same type of Deepmind system that learned to play dozens of Atari games, to superhuman levels, by watching the pixels, without any programmatic adaptation to the particular Atari game. At least the version of AlphaGo that played in October was far less specialized for Go than Deep Blue was for chess. Demis Hassabis says that next up after this is getti…
>> In case you're not aware, AlphaGo's key component is based on the same type of Deepmind system that learned to play dozens of Atari games, to superhuman levels, by watching the pixels, without any programmatic adaptation to the particular Atari game. The Atari-playing AI watched the pixels indeed, but it was also given a set of actions to choose from and more importantly, a reward representing the change in the ga…
I think you are confusing utility functions with intelligence. All AIs need utility functions. An AI without a utility function would just do nothing. It would have no reason to beat Atari games, because it wouldn't get any reward for doing so.
Even humans have utility functions. For example, we get rewards for having sex, or eating food, or just making social relationships with other humans. Or we have negative reinforcement from pain, and getting hurt, or getting rejected socially.
You can come up with more complicated utility functions. Like instead of beating the game, it's goal could be to explore as much of the game as possible. To discover novel things in the game. Kind of like a sense of boredom or novelty that humans have. But in the end it's still just a utility function, it doesn't change how the algorithm itself works to achieve it. AGI is entirely agnostic to the utility function.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#457The thing that was supposed to take at least 10 years happened. Only last month people were still saying that no way AlphaGo will beat the champion and that it will be crushed. Today everybody will have seen it coming and say that it was normal. Yet people will still tell that worrying about AI taking over is like worrying about overpopulation on Mars, and that this is a problem at least 50 years out.
I was one of the people who rooted for the champion last month, and my position hasn't changed. Last night's game was very exciting, but if the pressure doesn't get to Sedol he has a chance. He made some mistakes in the game and AlphaGo played incredibly well. General opinion I've seen so far is that the lead switched hands in a few places, although I'm waiting for professional commentaries to illuminate what possibilities were there for both players - the played game is always just the tip of the iceberg
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#458Earlier quoted context omitted.
I think it's fair to say that in the future, people will look back and wonder how it was possible to live without having a good AI.. similar to how we look past at caveman and wonder how they could live without electricity. AI is really just a tool that we leverage, the same was as we leveraged the wheel or electricity.
Yep. I was just talking with the founder of a startup I work with. His son was born in the past 5 months or so. The son is never going to live in a world that doesn't have deep learning. Like the kids who never knew what the world was like before the smartphone. Like the kids who never knew what the world was like before the web browser. And AI is just one strand. There are several strands that are as deeply changing…
The son is never going to live in a world that doesn't have deep learning.
Except if a big solar flare hits us ;}
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#459Earlier quoted context omitted.
> In go, beating someone 2/3 of the time corresponds to being about one kyu/dan rank stronger This isn't true. One kyu/dan rank stronger means being 1 stone stronger (so winning 50% of the time when playing White with reverse komi). In practice this may correspond to winning 2/3 of the time with normal komi for high dan players, but that doesn't hold for low kyu players. A 29k has maybe a 51% chance of winning agains…
Fair comment about very weak players. My impression is that the element of chance goes way down well before you get to high dan level, though. How sure are you that I'm wrong?
Quite sure. 17k players still make many huge mistakes, and at the other extreme, God (say 13d) would win 100% of the time against a 12d player. Given that the win ratio for a one rank difference starts at 50% for extreme beginners and ends at 100% for God, maybe you should be the one explaining why you'd expect a significant plateau at 2/3 instead of a smooth increase.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#460Earlier quoted context omitted.
> without having all of the training data in advance What? They certainly trained the algorithm on a huge database of professional go games. It's even in the abstract. [1] [1]: http://www.nature.com/nature/journal/v529/n7587/full/nature1...
> What? Exactly They used the game database to learn the value network, then reinforcement learning of the policy network was performed on self-play games. I.e., the machine learned to play from existing data, then played against itself to learn the search heuristics (the policy network) without the need for expert data.
Your claim still doesn't make sense. They either used expert data or they didn't. If the algorithm would lose when they remove the expert data, then they really do need expert data.
The tree search wasn't even the novel part of the algorithm... the authors even cite others who had used the identical technique in previous Go algorithms.