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We were discussing the probability that Sedol would win this game. Everyone, including me, bet 90% that no human would ever win again, let alone this specific g

We were discussing the probability that Sedol would win this game. Everyone, including me, bet 90% that no human would ever win again, let alone this specific game: http://predictionbook.com/predictions/177592 http://predictionbook.com/predictions/177592 I tried to estimate it mathematically. Using a uniform distribution across possible win rates, then updating the probability of different win rates with bayes rule. You can do that with Laplace's law of succession. I got a 20% that Sedol would win this game. However a uniform prior doesn't seem right. Eliezer Yudkowsky often says that AI is likely to be much better than humans, or much worse than humans. The probability of it falling into the exact same skill level is pretty implausible. And that argument seems right, but I wasn't sure how to model that formally. But it seemed right, and so 90% "felt" right. Clearly I was overconfident. So for the next game, with we use Laplace's law again, we get 33% chance that Sedol will win. 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 some chance he is now evenly matched with AlphaGo! I look forward to many future AI-human games. Hopefully humans will be able to learn from them, and perhaps even learn their weaknesses and how to exploit them. Depending how deterministic they are, you could perhaps even play the same sequence of moves and win again. That would really embarrass the Google team. I hear they froze AlphaGo's weights to prevent it from developing new bugs after testing.

jules 11y ago
The argument that AI is either much better or much worse does not apply here. It's not an accident that they chose this point in time to play against Lee Sedol instead of 10 years ago or 10 years in the future. They chose this point in time because they thought that they have a reasonable chance of winning. Also, he won with white but he will play with black next time, so playing the same sequence of moves can't happen. Additionally, even if the AI didn't incorporate any randomness in the opening (I think it does) it may choose different moves if it gets a different amount of time to think, so Lee Sedol would have to play his moves at exactly the same time as the last game. A couple of seconds deviation only has to lead to a different move in one of the 80 or so moves before the mistake was made to invalidate this strategy.
- CydeWeys 11y ago
  > It's not an accident that they chose this point in time to play against Lee Sedol instead of 10 years ago or 10 years in the future. They chose this point in time because they thought that they have a reasonable chance of winning. Most importantly, they chose this point in time because they know that there are several other AI research teams that are also on the right track (including at Facebook). Like circumnavigating the globe or landing on the Moon, 90% of the benefit of it is lost if someone else does it before you. So you don't wait for 100% certainty of winning -- you are maximizing for the chance of winning first, not winning for certain. Given that, it seems reasonable that they would go after Lee Sedol when they were sure they were better than him, but not too much better than him. So a non-5-0 outcome is, in hindsight, not horribly surprising.
- Houshalter 11y ago
  That kind of makes sense, however the point was more that AI progress isn't gradual and continuous. It's (sometimes) rapid and has discontinuities. Alphago was an entirely new method, using deep convolutional neural networks as a move generator. Therefore there wasn't any guarantee that it had to be just slightly better than previous Go playing algorithms, it could have easily been far above humans. Likewise this is also the first time Go AI has been given Google scale resources. Both in terms of a team of the best researchers working full time on it, and their computing power. Whereas previous Go projects were all hobbyist things. And Google didn't wait 10 years to challenge Sedol. The match was arranged only a few months at most after they started developing it.
taneq 11y ago
There are a lot of cases where humans are actually really close to optimal (one example is racing lines taken by F1 drivers being within tenths of a percent of perfect, don't have the link any more though sorry). In this case there are diminishing returns at play, and an AI which is a lot "stronger" than a human might still produce very similar results.

jules 11y ago

The argument that AI is either much better or much worse does not apply here. It's not an accident that they chose this point in time to play against Lee Sedol instead of 10 years ago or 10 years in the future. They chose this point in time because they thought that they have a reasonable chance of winning. Also, he won with white but he will play with black next time, so playing the same sequence of moves can't happen. Additionally, even if the AI didn't incorporate any randomness in the opening (I think it does) it may choose different moves if it gets a different amount of time to think, so Lee Sedol would have to play his moves at exactly the same time as the last game. A couple of seconds deviation only has to lead to a different move in one of the 80 or so moves before the mistake was made to invalidate this strategy.

CydeWeys 11y ago
> It's not an accident that they chose this point in time to play against Lee Sedol instead of 10 years ago or 10 years in the future. They chose this point in time because they thought that they have a reasonable chance of winning. Most importantly, they chose this point in time because they know that there are several other AI research teams that are also on the right track (including at Facebook). Like circumnavigating the globe or landing on the Moon, 90% of the benefit of it is lost if someone else does it before you. So you don't wait for 100% certainty of winning -- you are maximizing for the chance of winning first, not winning for certain. Given that, it seems reasonable that they would go after Lee Sedol when they were sure they were better than him, but not too much better than him. So a non-5-0 outcome is, in hindsight, not horribly surprising.
Houshalter 11y ago
That kind of makes sense, however the point was more that AI progress isn't gradual and continuous. It's (sometimes) rapid and has discontinuities. Alphago was an entirely new method, using deep convolutional neural networks as a move generator. Therefore there wasn't any guarantee that it had to be just slightly better than previous Go playing algorithms, it could have easily been far above humans. Likewise this is also the first time Go AI has been given Google scale resources. Both in terms of a team of the best researchers working full time on it, and their computing power. Whereas previous Go projects were all hobbyist things. And Google didn't wait 10 years to challenge Sedol. The match was arranged only a few months at most after they started developing it.

taneq 11y ago

There are a lot of cases where humans are actually really close to optimal (one example is racing lines taken by F1 drivers being within tenths of a percent of perfect, don't have the link any more though sorry). In this case there are diminishing returns at play, and an AI which is a lot "stronger" than a human might still produce very similar results.