Earlier quoted context omitted.
Welcome to the AI effect! Every time AI makes an accomplishment, it is disregarded. The goalposts are perpetually moved. "AI is whatever computers can't do yet." People said for years that Go would never be beaten in our lifetime. They said this because Go has a massive search space. It can't be beaten by brute force search. It requires intelligence, the ability to learn and recognize patterns. And it requires doing…
As far as I know the goal post of Turing test has never moved.
AlphaGo beats the world champion Lee Sedol in first of five matches
361–370 of 596 posts
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#362Can someone explain why this is more impressive than a computer beating top chess players over a decade ago? I'm not very familiar with Go, and while there were far more squares on a Go board, it seems less sophisticated than chess to me. Maybe Go has way more moves possible and emergent strategies or something I'm not taking into account.
"The game has long interested AI researchers because of its complexity...the average 150-move game contains more possible board configurations — 10^170 — than there are atoms in the Universe, so it can’t be solved by algorithms that search exhaustively for the best move." [Source: http://www.nature.com/news/google-ai-algorithm-masters-ancie... ]
208168199381979984699478633344862770286522453884530548425639456820927419612738015378525648451698519643907259916015628128546089888314427129715319317557736620397247064840935
to be precise. Which is more than even the square of the number of atoms in the universe, showing how silly that comparison is...Btw, the quoted "the average 150-move game contains" makes no sense at all, since such a game contains only 151 positions.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#363Isn't this jumping the shark a bit? It's a 5-game match. The first was really, really close.
I watched two 9d pro commentaries, Redmond's and Kim Myungwan's. Redmond was obviously being charitable in saying the game was close near the end. Myungwan said the victory was apparent several moves before the resignation, and Myungwan also said AlphaGo was clearly stronger than himself.
Either way, even if this game should be considered close, it's still not clear if AlphaGo was holding back in order to hold a secure win. It's possible it can play at a higher level, but it wasn't needed. We can't really know AlphaGo's strength until (if) it is beaten. The following matches will be very interesting.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#364Earlier quoted context omitted.
> The real world doesn't follow formal game rules. Really? Why not?
Infinite state/belief/world space. Infinite action space. It's not so much that there aren't rules (there are - physics), it's that the complexity of the full set of rules is exponential or super-exponential.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#365I posted in the earlier thread because this one wasn't up yet[1]. Some quick observations 1. AlphaGo underwent a substantial amount of improvement since October, apparently. The idea that it could go from mid-level professional to world class in a matter of months is kinda shocking. Once you find an approach that works, progress is fairly rapid. 2. I don't play Go, and so it was perhaps unsurprising that I didn't rea…
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#366Earlier quoted context omitted.
>The point is computation is an abstract concept and not tied to the physical medium that we use. That's not exactly true https://en.wikipedia.org/wiki/Limits_to_computation
Of course there are physical constraints on computing, but measuring by weight is rather stupid. Measuring the energy consumption seems to be a way better metric (even though "computation per energy" is clearly a human win). Not to mention that we suddenly forgot that computers have their own units of measurement, such as clock speed (hertz) and memory size (bytes).
Is it? The problem here is it is really hard to compare the TCO. For example prime human computation requires years and years of learning and teaching, in which the human cannot be turned off (this kills the human). A computer can save its state and go in a low or even a zero power mode.
>such as clock speed (hertz) and memory size (bytes).
Which are completely meaningless, especially in distributed hybrid systems. Clock speed is like saying you can run at 10 miles per hour, but it doesn't define how much you can carry. GPUs run a far slower clock speed than CPUs, but they are massively parallel and are much faster than CPUs on distributed workloads. Having lots of memory is important, but not all memory is equal and hierarchy is even more important. Computer memory is (hopefully) bit perfect and a massive amount of power is spent keeping it that way. That is nice when it comes to remembering exactly how much money you have in the bank. Human memory is wonderful and terrible at the same time. There is no 'truth' in human memory, only repetition. A computer can take a picture and then make a hash of the image, both of which can be documented and verified. A human can recall a memory, but the act of recalling that memory changes it, and the parts we don't remember so well are influenced by our current state. It is this 'inaccuracy' that helps us use so little power for the amount of thinking we do.
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#367Earlier quoted context omitted.
"The game has long interested AI researchers because of its complexity...the average 150-move game contains more possible board configurations — 10^170 — than there are atoms in the Universe, so it can’t be solved by algorithms that search exhaustively for the best move." [Source: http://www.nature.com/news/google-ai-algorithm-masters-ancie... ]
208168199381979984699478633344862770286522453884530548425639456820927419612738015378525648451698519643907259916015628128546089888314427129715319317557736620397247064840935 to be precise. Which is more than even the square of the number of atoms in the universe, showing how silly that comparison is... Btw, the quoted "the average 150-move game contains" makes no sense at all, since such a game contains only 151 positi…
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#368I posted in the earlier thread because this one wasn't up yet[1]. Some quick observations 1. AlphaGo underwent a substantial amount of improvement since October, apparently. The idea that it could go from mid-level professional to world class in a matter of months is kinda shocking. Once you find an approach that works, progress is fairly rapid. 2. I don't play Go, and so it was perhaps unsurprising that I didn't rea…
Since the European match went 5-0, how do we know the bot wasn't just as good months ago?
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#369Earlier quoted context omitted.
As far as I know the goal post of Turing test has never moved.
Chatbots can already beat the turing test.
(the answer is Rocky Road by the way)
Re: AlphaGo beats the world champion Lee Sedol in first of five matches
#370I was at the 2003 match of Garry Kasparov vs Deep Junior -- the strongest chess player of all time vs what was at that point the strongest chess playing computer in history. Kasparov drew that match, but it was clear it was the last stand of homo sapiens in the man vs machine chess battle. Back then, people took solace in the game of Go. Many boldly and confidently predicted we wouldn't see a computer beat the Go wor…
AlphaGo's architecture resembles much closer to how humans think and learn.
I initially learned Go to be able to have some chance of an AI. I then had some transformative experiences that coincided with my early kyu learning of basic Go lessons. On of the big lessons in Go is to learn how to let go of something. Taking solace in anything on the Go board is one of the blocks you work through when you develop as a Go player.
I had already known about two years ago that just the Monte Carlo approach was already scalable. If Moore's Law continues, it was a matter of time before the Monte Carlo approach would start challenging the professional ranks -- it had already gotten to the point where you just needed to throw more hardware at it.
AlphaGo's architecture adds a different layer to it. The Deep Learning isn't quite as flexible as the human mind, but it can do something that humans can't: learn non-stop, 24/7 on one subject. We're seeing a different tipping point here, possibly the same kind of tipping point when we witnessed the web browser back in the early 90s, and the introduction of the smartphone in the mid '00s. This is way bigger (to use a Go terminology) than what happened with chess.