what??

In an interview Demis said that AlphaGo thought (so many anthropomorphisms!) the chance of white playing the L11 wedge was less than 1 in 10,000 (probability from policy network?), so it won't have been in many of its play-outs and evaluations before Lee played it (I believe MCTS can re-use information from analysis on previous moves in the game, so there won't have been as much already existing analysis for this unexpected move). Something I noticed when watching the stream is AlphaGo/Aja seemed to play k10 even more quickly than normal, does anyone have precise move timings? When a human faces an unexpected move they usually spend extra time to see if there was something they missed, but I wonder if here by being an unexpected move there was very little existing analysis of continuations from L11 so when it then spent 30 seconds or whatever on it that was essentially the only reading of it, whereas for other moves it has expected you get the 30 seconds of clock time plus this huge backlog of existing analysis from previous moves, and consequently was much weaker reading than normal.

P.S. I do find it odd Younggil didn't see L10, to me atari on top was my first instinct, then from below.

Quite apparently, AlphaGo does not have a face-washing mode ...

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Certainly mine too (beginners play atari!). Maybe it means that he dismissed it?

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Chart of time taken: http://imgur.com/3HcJKbk AlphaGo took it's usual ~1 minute to answer the wedge. Also from Hassabis' tweet during the match:


BTW after this tweet during the press conference he changed his wording to emphasize the brilliance of Lee's wedge 78, and saying that AlphaGo got confused. I haven't seen calling AlphaGo's 79 a mistake since then. I think this is (good) PR spin by Hassabis who has consistently praised Lee.

Hassabis also said AlphaGo's evaluation didn't drop until move 87. So it's very unlikely that simply thinking harder on move 79 would have helped, the position was too unclear too deep into the tree for AlphaGo to read. OTOH it does seem to show that AlphaGo doesn't increase it's thinking time just because the opponent makes an unexpected move. From the time chart you can see it increased it's thinking time for move 87. That would be consistent with it thinking longer on turns when the evaluation of the position changes suddenly.

If I remember correctly, Hassabis in the press conference said that AlphaGo was pressured into making a mistake. I found it odd that he would say it was pressured. One of the strengths of the program is that it is not pressured, but it is also its weakness, in that if Lee played the same moves as White again, the computer would likely repeat all the same moves as Black and make the same mistake.

AlphaGo does not read and this is the reason why it lost at this moment: it did not verify by reading. The AlphaGo team is too focused on neural nets.

Wrong. It uses MCTS for reading.

MCTS is NOT reading. It is incomplete sampling with "arbitrary" gaps and without complete decision-making down the tree.

[Tactical] reading means functionally complete tree exploration and decision-making down the tree. (Obvious failures and obviously inferior moves may be ignored but all interesting or unclear moves must be read unless pruned by the reading method / principles.)

EDITED

By your definition then I and other humans don't read either, as our reading is not perfect or "functionally complete tree exploration and decision-making down the tree". Perhaps you meant AlphaGo did not read correctly, that is different from AlphaGo does not read.

In fact, it is a weakness of many human players that their local tactical reading, which should be functionally complete, is incomplete. With greater effort, they can make it complete.

They kind of sort of did OK, some people would say. Must try harder, naturally.

It is true that MCTS is not the same thing as reading, at least in the same sense as we humans typically read.
However, AlphaGo DOES read similarly to how we do it, going down a tree of moves and then evaluating whether the resulting position is favorable/unfavorable. It does that using the value network, while humans rely on judgement.

The Nature paper explained that the results of the MCTS and of the value network were combined 50%/50% in order to assess the quality of a move. I think it is likely that some part of this changed in the past 6 months, but as far as we know, AlphaGo DOES read in a very similar way that humans do.

Arguably no one has made it complete by your assumptions.

Understatement of the year...(emphasis mine)

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I didn't see this posted yet, but Haylee explains the move pretty well in her review starting at about 1:09

https://youtu.be/482sitMhspo?t=1h9m