Comment by fhe | Hacker News Reader

Comment by fhe | Hacker News Reader

My friends and I (many of us are enthusiastic Go lovers/players) have been following all of the games closely. AlphaGo's mid game today was really strange. Many experts have praised Lee's move 78 as a "divine-inspired" move. While it was a complex setup, in terms of number of searches I can't see it be any more complex than the games before. Indeed because it was a very much a local fight, the number of possible moves were rather limited. As Lee said in the post-game conference, it was the only move that made any sense at all, as any other move would quickly prove to be fatal after half a dozen or so exchanges.

Of course, what's obvious to a human might not be so at all to a computer. And this is the interesting point that I hope the DeepMind researchers would shed some light on for all of us after they dig out what was going on inside AlphaGo at the time. And we'd also love to learn why did AlphaGo seem to go off the rails after this initial stumble and made a string of indecipherable moves thereafter.

Congrats to Lee and the DeepMind team! It was an exciting and I hope informative match to both sides.

As a final note: I started following the match thinking I am watching a competition of intelligence (loosely defined) between man and machine. What I ended up witnessing was incredible human drama, of Lee bearing incredible pressure, being hit hard repeatedly while the world is watching, sinking to the lowest of the lows, and soaring back up winning one game for the human race.. Just incredible up and down in a course of a week. Many of my friends were crying as the computer resigned.

Given the 78 was a "divine inspired" move, and Demis tweeted that AlphaGo's mistake was move 79, my guess is that Black 78 was not in AlphaGo's search tree at all. It had pruned that move as being too "unlike what a human pro would do", and had not considered play beyond that point. Then it had to suddenly backtrack, drop its entire search tree, and start rebuilding from scratch. It took only a couple minutes to do so, but that's still not enough time to build up the depth and breadth of a tree that it had been constructing up to that point in the game. So it ended up playing a suboptimal move simply because Lee Sedol played a move that was simultaneously brilliant/strong and novel/unexpected, and it had to respond somehow.

The problem may well have occurred before then, too. If move 78 was incorrectly pruned from the tree for being unlikely, then AlphaGo had many turns in which it should have been considering counter-moves to move 78 (and thus prevent the situation that allowed move 78 to even happen in the first place), but it didn't.

>"divine-inspired" move

Just letting others know, this expression is a rather common way of saying a single move that changed the course of the game. There were "divine-inspired moves" that AlphaGo made in the first three games too.

Well it's not exactly common. It's used to describe the very best moves at the highest level of play.

I mean yeah, the decisive move _I_ make when I play my noob games is hardly divine, but in top level play, it happens every game.

AlphaGo's mid game today was really strange. Many experts have praised Lee's move 78 as a "divine-inspired" move.

Add to that the moves where AlphaGo basically threw away stones by adding to formations that would be removed from the table. Even I, a complete, lousy, amateur, could see that they were a mistake.

To be fair, those moves were made when AlphaGo was already behind. It's just not any good at dealing with being that far back. The AI just has no concept of what to do while behind: What a human would do is to go for positions that are very complicated, making the chances of sloppy play much higher. Instead, it makes moves that have to be answered in only one or two ways, but that are very easy to read by even an amateur human.

Training an ai to make good play in a bad situation would require it to train in ways that are very different than the AlphaGo vs AlphaGo training that it spent a lot of time doing. And why do that, instead of trying to make itself good while the game is even, or when it's winning?

It's a bit like how it's different to train in chess to play in pro games, vs training to hustle amateurs in the park: You are not making the best move, but a good move that will confuse the opponent the most. You are trying to exploit a bad opponent: Very different play.

Crying tears of joy I hope... or are your friends computers?

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