191–200 of 576 posts
Let's compare Go and Chess. We all know that Go is more complex that Chess, but how much more? There's 10^50 atoms in the planet Earth. That's a lot. Let's put a chess board in each of them. We'll count each possible permutation of each of the chess boards as a separate position. That's a lot, right? There's 10^50 atoms, and 10^40 positions in each chess board so that gives us 10^90 total positions. That's a lot of p…
Someone somewhere asked why a lot of people in the Go community is taking this in a somewhat hard way, here is my hypothesis: Go, unlike Chess, has deep mytho attached to it. Throughout the history of many Asian countries it's seen as the ultimate abstract strategy game that deeply relies on players' intuition, personality, worldview. The best players are not described as "smart", they are described as "wise". I thin…
On a more realistic side note... Professional Go players devote decades in training ever since their youth, giving up normal educations and lots of other more lucrative opportunities for their lives. It's very easy to imagine their frustrations now that their life-time devotion actually means nothing in front of the AI. It's an upright denial to the way of life they so chose and devoted. IMHO Google should donate the…
I don't think people will pay to watch Go Bots square off, but I think this example of "obsolete education" is a great reminder that it's not just the assembly line jobs on the chopping block.
Someone somewhere asked why a lot of people in the Go community is taking this in a somewhat hard way, here is my hypothesis: Go, unlike Chess, has deep mytho attached to it. Throughout the history of many Asian countries it's seen as the ultimate abstract strategy game that deeply relies on players' intuition, personality, worldview. The best players are not described as "smart", they are described as "wise". I thin…
AlphaGo did paradigm shifting moves.
Earlier quoted context omitted.
AFAIK Mechanical Turk is just getting random people to do stuff for you - the concept of Focus is something else entirely and genuinely quite terrifying.
The book is on my reading list. I guess I'll have to bump it closer to the front, then.
Let's compare Go and Chess. We all know that Go is more complex that Chess, but how much more? There's 10^50 atoms in the planet Earth. That's a lot. Let's put a chess board in each of them. We'll count each possible permutation of each of the chess boards as a separate position. That's a lot, right? There's 10^50 atoms, and 10^40 positions in each chess board so that gives us 10^90 total positions. That's a lot of p…
This doesn't seem to be the main reason why Go is harder than chess for computers. It was noted that even in 9x9 Go, with a comparable branching factor to Chess, traditional Go programs are still no stronger than on big boards. The main difficulty for Go is that it is much harder to evaluate board positions. So in Chess the depth of the search can be significantly reduced by using a reasonable evaluation function, wh…
Are they not? MoGo beat pros of 9 Dan on 9x9 in 2011: https://www.lri.fr/~teytaud/mogo.html
Earlier quoted context omitted.
I mean it's not clear in anyway "where" is the intuition, it just sort of magically emerges from the connections and the weights in a way that no one can really grasp. If nothing else, just due to the sheer number of neurones.
Is this just something you're imagining, or did Google's developers explicitly say, "AlphaGo is beyond our understanding. We have absolutely no idea how it makes its decisions"?
They can see certain stats and high level overview.
But they have no idea what it's thinking.
They know the general pattern of the algorithm. They even explain it.
But the algorithm involves two deep neural networks, and they don't really know what's going on inside them.
One of the developers showed up during the commentary on the second game and talk about this stuff:
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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…
> all the players will simultaneously consider the same branches 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!
Is there a meaningful response that each one could give that would be optimal? I figure this would only stand a chance of working if the pool of humans were cloned from a 9 dan :-)
Someone somewhere asked why a lot of people in the Go community is taking this in a somewhat hard way, here is my hypothesis: Go, unlike Chess, has deep mytho attached to it. Throughout the history of many Asian countries it's seen as the ultimate abstract strategy game that deeply relies on players' intuition, personality, worldview. The best players are not described as "smart", they are described as "wise". I thin…
Art is, mostly, domain of knowledge not yet claimed by science. When a technique turns art into science, it means that humans are ready to tackle even harder problems. Think about medicine before and after microscopes. Holy art turned into boring science: huge win for human race. If an AI won the next Hugo award, I would be rejoiced. It wouldn't mean the end of literature at all; it would mean that humans are ready t…
https://en.m.wikipedia.org/wiki/Emily_Howell
We have all kinds of visual art made by computers and AI - prom painting from photos to abstract art to 3D renders.
We have computers writing poems and haiku.
The only thing that's missing is the conceptual creation, which, let's be honest, most human artists struggle at as well. So writing and interesting story is not yet in the AI's domain.
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Fan Hui has already learned from AlphaGo. He's been playing matches against her regularly, and (perhaps as a result of that) won _all_ his games in the last European championship.
Interesting. Mind if I ask for a source? Where did you read this?
Earlier quoted context omitted.
Actually this AI kind of confirms these myths, since its basis are not in mathematics but in neural networks. While it could be argued to be just math, so is the brain, but that's besides the point. The point is, even the programmers have no idea what the AI is thinking. The way it picks moves is very similar to how top professionals do. Intuition is reduced to memories stored vaguely as neural connections.
I fear this is an overly mystical misinterpretation of neural nets. (Standard feed-forward) neural nets are layers of non-linear feature transformations. They take inputs and at each step transform those inputs into a more compact representation, distilling the inputs into their most important factors (and throwing away unimportant factors). So the most likely explanation is that policy/value nets in AlphaGo have lea…
I don't think that's an entirely accurate way of putting it, because a player who reaches that level is also doing a little tree searching. Maybe if you found some human who managed to reach "amateur pro" level by playing purely on snap, instinctual decisions without any logic or exploration of variants at all, yes, then you could say their ability to evaluate positions is as good as AlphaGo's.
But I would guess that you are right anyway that we can deduce that its ability to evaluate a board position really is below that of better professionals, and its huge strength is due to the tree search (which of course involves a second "policy" net to pick moves to explore).