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Chess requires understanding, which computers lack. Go requires understanding, which computers lack. X requires Y which AI technology today lacks. AI is a const

by atrus 3y ago

Chess requires understanding, which computers lack. Go requires understanding, which computers lack. X requires Y which AI technology today lacks. AI is a constantly moving goalpost it seems.

satvikpendem 3y ago
> AI is a constantly moving goalpost it seems. alwayshasbeen.png > The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.[1] > Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'."[2] Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"[3] > "AI is whatever hasn't been done yet." > —Larry Tesler https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect
The_Colonel 3y ago
It was always clear that games like chess or go can be played by computers well, even with simple algorithms, because they were completely formalized. The only issue was with performance / finding more efficient algorithms. That's very different from code which (perhaps surprisingly) isn't well formalized. The goals are often vague and it's difficult to figure out what is intentional and what incidental behavior (esp. with imperative code).
- apetresc 3y ago
  > It was always clear that games like chess or go can be played by computers well As someone who was deeply involved in the Go scene since the early 2000s let me emphatically assure you it was not at all clear. Indeed it was a major point of pride among Go enthusiasts that computers could not play it well, for various reasons (some, like the branching factor, one could potentially grant that advances in hardware and software could solve for eventually. Others, like the inherent difficulty in constructing an evaluation function, seemed intractable). Betting markets at the time of the AlphaGo match still had favorable odds for Sedol, even with the knowledge that Google was super-confident baked in. It is extreme hindsight-bias of exactly the type the grandparent was talking about to suggest that obviously everybody knew all along that Go was very beatable by "non-real AI".
  - The_Colonel 3y ago
    > Indeed it was a major point of pride among Go enthusiasts that computers could not play it well It's typical for enthusiast of anything to believe their area is special. To be able to judge how feasible besting humans is a question for computer scientists / engineers anyway. You need some knowledge of Go for sure, but don't actually have to be a master Go player. > It is extreme hindsight-bias of exactly the type the grandparent was talking about to suggest that obviously everybody knew all along that Go was very beatable by "non-real AI". Maybe it was a surprise for you, but I was familiar with the pre-AlphaGo state of the art, and it was always clear it's just a technical problem. There's no fundamental difference between a game like Go and Chess, it's only the parameters which differ, where Go's space is exponentially larger. > Others, like the inherent difficulty in constructing an evaluation function, seemed intractable The branching factor is what makes the evaluation function difficult in Go and is therefore again a technical problem. > Betting markets at the time of the AlphaGo match still had favorable odds for Sedol, even with the knowledge that Google was super-confident baked in. This is a non-argument, betting markets are not rational.
arp242 3y ago
> Chess requires understanding Actually it doesn't, as demonstrated by the fact that people have made fairly decent chess implementations in 1K lines of code and things like that. Chess is comparatively easy because it has well-defined rules and well-defined concepts of "good" and "bad". Refactoring something to be multi-threaded is incomparably more complex and any comparison to this is just pointless.

by atrus 3y ago

Chess requires understanding, which computers lack. Go requires understanding, which computers lack. X requires Y which AI technology today lacks. AI is a constantly moving goalpost it seems.

satvikpendem 3y ago

> AI is a constantly moving goalpost it seems. alwayshasbeen.png > The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.[1] > Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'."[2] Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"[3] > "AI is whatever hasn't been done yet." > —Larry Tesler https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect

The_Colonel 3y ago

It was always clear that games like chess or go can be played by computers well, even with simple algorithms, because they were completely formalized. The only issue was with performance / finding more efficient algorithms. That's very different from code which (perhaps surprisingly) isn't well formalized. The goals are often vague and it's difficult to figure out what is intentional and what incidental behavior (esp. with imperative code).

apetresc 3y ago
> It was always clear that games like chess or go can be played by computers well As someone who was deeply involved in the Go scene since the early 2000s let me emphatically assure you it was not at all clear. Indeed it was a major point of pride among Go enthusiasts that computers could not play it well, for various reasons (some, like the branching factor, one could potentially grant that advances in hardware and software could solve for eventually. Others, like the inherent difficulty in constructing an evaluation function, seemed intractable). Betting markets at the time of the AlphaGo match still had favorable odds for Sedol, even with the knowledge that Google was super-confident baked in. It is extreme hindsight-bias of exactly the type the grandparent was talking about to suggest that obviously everybody knew all along that Go was very beatable by "non-real AI".
- The_Colonel 3y ago
  > Indeed it was a major point of pride among Go enthusiasts that computers could not play it well It's typical for enthusiast of anything to believe their area is special. To be able to judge how feasible besting humans is a question for computer scientists / engineers anyway. You need some knowledge of Go for sure, but don't actually have to be a master Go player. > It is extreme hindsight-bias of exactly the type the grandparent was talking about to suggest that obviously everybody knew all along that Go was very beatable by "non-real AI". Maybe it was a surprise for you, but I was familiar with the pre-AlphaGo state of the art, and it was always clear it's just a technical problem. There's no fundamental difference between a game like Go and Chess, it's only the parameters which differ, where Go's space is exponentially larger. > Others, like the inherent difficulty in constructing an evaluation function, seemed intractable The branching factor is what makes the evaluation function difficult in Go and is therefore again a technical problem. > Betting markets at the time of the AlphaGo match still had favorable odds for Sedol, even with the knowledge that Google was super-confident baked in. This is a non-argument, betting markets are not rational.

arp242 3y ago

> Chess requires understanding Actually it doesn't, as demonstrated by the fact that people have made fairly decent chess implementations in 1K lines of code and things like that. Chess is comparatively easy because it has well-defined rules and well-defined concepts of "good" and "bad". Refactoring something to be multi-threaded is incomparably more complex and any comparison to this is just pointless.