skarist

This is of course all very, very impressive, but it would be great to see more details on this. We are told AZ only started with the basic rules. What was included in the "basic rules"? How were they codified? The engine looks at 80.000 positions at second, so obviously it has some evaluation function. What is the position evaluation function? Presumably it was codified in some way in the beginning, and then got improved by the training period? It would be very interesting to see the first 100 games, or so, the engine it played against itself.

Good list. However, I notice lack of movies from such great directors as Wim Wenders and Andrei Tarkovsky. Well, I guess it is difficult to put together a list like this anyway.

Great game and amazing series/match. This last one was absolutely nail biting. My hat off to the AlphaGo team and to Mr. Lee Sedol. Sedol showed incredible fighting spirit and stamina. Just imagine sitting through a 5 hour game like that last one, with full concentration all the time. And seeing the expression of exhaustion and disappointment on Sedol's face after last moves and his resignation. Phew... I bet that he came in rather confident into this last game, after beating AlphaGo in the fourth, figuring he had found a weakness. And he seemed to have a rather good start, securing a decent territory in the lower right corner. We can all marvel at the machine/software the DeepMind team has built, but still I feel that the real marvel is the human brain. Will we learn anything from this series, about how it functions and evaluates game positions in a stratetgic games? The classic problem/mystery is how extremely good the human brain is at pruning game-trees. Whole branches are thrown out in split seconds and probably never explored. Currently taking a watt-for-watt comparison there is no question about whose "hardware" is superior -> Lee Sedol's brain. But I guess the DeepMind team and the community will take plenty of lessons from this and in a few years span, Lee Sedol's phone will beat him 100% of the time. At least I wouldn't be willing to bet against it, even though we are hitting the roof in Moore's law.

Yes... as is John McDowell, Crispin Wright, John Searle and Alvin Plantinga.

While I would agree that his interpretation of Wittgenstein on following a rule and private language, is wrong as such, i.e. as an interpretation, it is definitely very interesting and thought provoking stuff. It is good philosophy and bears good witness to the creative genius of Kripke.

Most definitely.

A great thinker has passed. One of the great names of 20th century analytical philosophy. They have now all left us, Quine, Rorty, Davidson and now Putnam. RIP.

I guess they had a similar event on Twin Earth... even though their "water" may be a bit different from our H2O.

We are indeed witnessing and living a historic moment. It is difficult not to feel awestruck. Likewise, it is difficult not to feel awestruck at how a wet 1.5 kg clump of carbon-based material (e.g. Lee Sedol brain) can achieve this level of mastery of a board game, that it takes such an insane amount of computing power to beat it. So, finally we do have a measure of the computing power required to play Go at the professional level. And it is immense, or to apply a very crude approximation based on Moore's law, it requires about 4096 times more computing power to play Go at the professional level than it does to play chess. Ok, this approx may be a bit crude :)

But maybe this is all just human prejudice... i.e. what this really goes to show is that in the final analysis all board games we humans have inveted and played are "trival", i.e. they are all just like tic-tac-toe just with a varying degree of complexity.

I predict 5-0 for DeepMind. Now, Lee has a broken self-confidence to battle (crucial for a human player), something that will not and can not trouble the DeepMind team.