181–190 of 471 posts
Earlier quoted context omitted.
Don't post unfounded conspiracy theories if you don't want to sound like a conspiracy theorist.
A lot of comments here are unfounded. It was a thought I had that imo warrants some discussion (which you may disagree)
How could DeepMind prove that AlphaGo played its best in match 4 ?
So AlphaGo is just a bot after all... Toward the end AlphaGo was making moves that even I (as a double-digit kyu player) could recognize as really bad. However, one of the commentators made the observation that each time it did, the moves forced a highly-predictable move by Lee Sedol in response. From the point of view of a Go player, they were non-sensical because they only removed points from the board and didn't a…
Maybe its training was focused on winning, not loosing narrowly. So as soon as it became obvious it can't win. It was just making silly moves because it was less researched scenario.
Some people when they see they can't win they do silly moves just for fun.
Bizarre. I felt a palpable sense of relief when I read this. Silly meat-brain that I am.
A living brain is made of neural nano-processors.
If it's true that AlphaGo started making a series of bad moves after its mistake on move 79, this might tie into a classic problem with agents trained using reinforcement learning, which is that after making an initial mistake (whether by accident or due to noise, etc.), the agent gets taken into a state it's not familiar with, so it makes another mistake, digging an even deeper hole for itself - the mistakes then co…
There is a possibility that the AlphaGo team, knowing that it has already won a decisive victory, wanted to spare the champion a crushing 5-0 defeat and so commanded the AI to lose on purpose.
Bizarre. I felt a palpable sense of relief when I read this. Silly meat-brain that I am.
Living flesh is not meat. Meat is what we call dead flesh. A living brain is made of neural nano-processors.
AlphaGo made a mistake and realized it was behind, and crumbled because all moves are "mistakes"(they all lead to loss) so any of them is as good as any other.
Im very suprrised and glad to see Humans still have something against AlphaGo, but ultimately, these kind of errors might dissapear if AlphaGo trains 6 more months. It made a tactical mistake, not a theory one.
Apparently AlphaGo made two rather stupid moves on the sidelines, judging from the commentary. Which incidentally is the kind of edgecase one would expect machine learning against itself is bad at learning, since there is a possibility that AlphaGo just tries to avoid such situations. It will be interesting to see if top players are able to exploit such weaknesses once AlphaGo is better understood by high level Go pl…
From my perspective as a weak player, those stupid moves are the sorts of moves I would make if I already knew I was losing (but not by a huge margin, otherwise resign) but I was in byo-yomi overtime. It settles already dead stones and gives me a bit more time to keep searching for a better move that could maybe turn the game around, and if the opponent fails to make the obvious response then I can turn the game arou…
Earlier quoted context omitted.
I would avoid thinking of this like a traditional computer program that just "bugged out" due to a glitch or a problem in the software. More accurately, it failed to account for the implications of a move on the board and therefore focused its attention in the wrong place. This happens often in games, I can imagine that a chess master playing an amateur might move his knight or bishop into a position that does immedi…
I mean that it bugged out because the moves it made after missing the exchange in the middle were moves that were obviously wrong, not in a "maybe it's up to something" kind of way, but in an objectively 100% bad kind of way. Even if you can't analyze all possibilities AlphaGo made a number of moves that made absolutely no sense at all even to way lower level players.
Another possibility is that it was looking way deeper than anybody, and there was a 1% chance or turning the whole game around with those seemingly bad moves. But Lee Sedol blocked that deep move in a way nobody was able to see.
Relevant tweets from Demis; Lee Sedol is playing brilliantly! #AlphaGo thought it was doing well, but got confused on move 87. We are in trouble now... Mistake was on move 79, but #AlphaGo only came to that realisation on around move 87 When I say 'thought' and 'realisation' I just mean the output of #AlphaGo value net. It was around 70% at move 79 and then dived on move 87 Lee Sedol wins game 4!!! Congratulations! H…