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Comment by carlmr | Hacker News Reader

I think you're right, but the implication is still that the AI often learns very specific strategies, whereas humans understand the game rules and then learn how to play within those rules.

The AI, despite its large training set, did not learn the rules of the game properly, as shown by this scoring mistake. And I do think the implications for other AIs failing spectacularly are quite notable. We've seen this before with AIs being able to find the tiniest of tumors, but then failing on a tumor that fills half the screen.

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It's kind of weird: looking at the board in the article as a Go player, I would say the game is over and white won. But they're using a ruleset (Tromp-Taylor) which is commonly used in computer Go but almost never between humans, precisely because it requires you to play past the point where it's completely obvious that the game is decided.

So it's not clear that humans understand the rules and computers do not: humans play a slightly different game than the rules the AI is being evaluated against.

> whereas humans understand the game rules

I'm not so sure it's that simple. The "understanding" a humans have is build upon knowing thousands of strategies. Does a person understand chess if he knows the rules but has never played or seen an actual game? I would say no. In some way I argue the AI understands Go better then any human since it mostly defeats humans. That there are strategies that work well against it doesn't mean it doesn't understand the game. Humans miss obvious things all thr time too.

I think the AI did learn the game correctly though. It's reasonable for white to pass assuming the black stones in its territory are dead. It's reasonable for black to pass assuming that it cannot make its stones in white's territory live. The only unreasonable thing is the scoring which incorrectly counts the dead black stones as alive.

I believe that human players would also pass in this situation.

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