81–90 of 576 posts
Earlier quoted context omitted.
To address this, has anyone considered pitting AlphaGo against a team of 9p players consulting with each other, and perhaps taking charge of different conflicts on the board?
I can't find the source now, but I remember reading a while ago that a team of go players is, perhaps contrary to intuition, not significantly better than their strongest individual alone. There's just no useful way to "pool" human thinking power and redistribute it to where it's needed the most – all the players will simultaneously consider the same branches. At best you reduce the risk of making a silly mistake, bu…
A computer-assisted pool of humans might work. Feed each human a board state advanced by 1/2/3/N moves down the decision tree in some direction, and have them evaluate that particular sub-tree. It's a map-reduce problem!
The next person that will beat alphaGo may not be a top go player. In particular, I'm wondering if a computer scientist with access to the alphaGo source code and all the weights of the network could trick alphaGo in order to win games automatically (cf. the papers that show a neural net can be tricked to classify a plane as any other class). If a human with the knowledge of the source code and the weights can do thi…
I had this conversation earlier with a friend wondering if any of Sedol's Korean pro buddies have noticed any systematic biases that could be exploited. I think it would be possible to make the neural net relatively useless by playing strange sequences that hack the weights, but you're still left with a monte-carlo-tree-search bot which alone depending on its implementation is between 2d and 6d amateur (so on the far…
Earlier quoted context omitted.
The 9p commentator at the AGA channel said you should judge genius versus madness on whether alphago won. And it did.
The "mad" moves could also be throwing the human off. I wonder how Sedol would fare given a year or so of practice against AlphaGo.
Lee Sedol seemed to be doing well before he went into extra time (as far as I could follow from the commentators). How is it ensured that this is a fair game given the time constraints? I'm guessing adding more computing power to the AlphaGo program should definitely help it in this regard.
> How is it ensured that this is a fair game given the time constraints? Both players get the same time controls, seems fair to me But if you're saying humans might fare better against computers in a game with a longer time control, I suspect that's true
I find it very interesting that to a layperson, the idea of a computer being able to beat a human at a logic game is pretty much expected and uninteresting. You try and share this story with a non-technical person and they will likely say "Well, duh..it's a computer".
Pitch it as a creativity game rather than a logic game. I mean, it's a little bit of both, right?
I mean, deep down, Go is a perfect-information-zero-sum-discrete-2-player game.
I think a more successful pitch is showing that the strategies and skills coming from Go (human or robot) can be useful outside the game, as I argue here: http://rare-technologies.com/go_games_life/
Tonight's game was beautiful. Last night's was a fighting game way too high level for me to really grasp (I have no idea how to play like that, all those straight and thin groups would make me nervous). I'm expecting Sedol to win Friday since I imagine he's going to have a great study session today, but I'm no longer confident he'll win the last two.. Still rooting for him though. :) (I also want to see AlphaGo play Ke Jie (ed: sounds like from the other submission on Ke's thoughts that may happen if Sedol is soundly defeated), and for kicks play Fan Hui again and see whether it now crushes weaker pros or is strangely biased to adopt a style just slightly stronger than who it's facing.)
Lee Sedol seemed to be doing well before he went into extra time (as far as I could follow from the commentators). How is it ensured that this is a fair game given the time constraints? I'm guessing adding more computing power to the AlphaGo program should definitely help it in this regard.
Maybe the budget should be energy rather than time?
Unless you're not counting support systems, in case it becomes very complicated to calculate and decide exactly which energy expenses are for support systems and which are directly integral for function.
Earlier quoted context omitted.
To address this, has anyone considered pitting AlphaGo against a team of 9p players consulting with each other, and perhaps taking charge of different conflicts on the board?
I can't find the source now, but I remember reading a while ago that a team of go players is, perhaps contrary to intuition, not significantly better than their strongest individual alone. There's just no useful way to "pool" human thinking power and redistribute it to where it's needed the most – all the players will simultaneously consider the same branches. At best you reduce the risk of making a silly mistake, bu…
Of course, Go has way too many eligible possible moves for random people to vote on, but a large enough group of top pros might be able to do well just by voting.
I find it very interesting that to a layperson, the idea of a computer being able to beat a human at a logic game is pretty much expected and uninteresting. You try and share this story with a non-technical person and they will likely say "Well, duh..it's a computer".
I encountered this many times over the past couple of days haha. I then have to explain that previous AIs, like those in chess largely used brute force computation to simulate each move, while these AIs "actually learn, similar to our brain". Probably not the most scientific explanation, but I feel your sentiment.
Is it that the deep net works mainly as an evaluation function of the current position? I guess it does more than that right?