4 ms·

On the other hand i would like to read an assessment of the significance of this advance. While AI may have perfect applicability to these perfect information g

by return0 11y ago

On the other hand i would like to read an assessment of the significance of this advance. While AI may have perfect applicability to these perfect information games, we may still be decades from useful real world generic applications.

partycoder 11y ago
It is good enough now to replace millions of jobs. Transportation, retail, press, trading, etc. It is also good enough to put it in a combat drone that visually recognizes objectives and people. This can be all commanded by a small group of people, anonymously, and detached from accountability and without casualties.
- scarmig 11y ago
  Well, no casualties among the people ordering the AI. Kids going to their aunties' wedding, a bit less so. To say nothing of the casualties that'll be inflected on the AI warriors...
  - hutzlibu 11y ago
    I guess, he was aware of that ...
nzonbi 11y ago
In my opinion a possible path is to make some sort of Symbolic AI (https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence https://en.wikipedia.org/wiki/Symbolic_artificial_intelligen...) system, and put machine learning on top, and even below of it. You could start with a very basic Symbolic AI, easier to understand. Then growth it gradually. The cool thing of this approach, would be that you could inspect the symbolic system to get a glance at how the AI system is thinking. Obviously a purely neuronal system can also do the trick. That is how the human brain works. But it would be great to make a system based on a symbolic AI, because it could be very interesting to observe its inner working. And it would also be possible to interact with it at the symbolic level.
- deleted 11y ago
  [deleted]
- tim333 11y ago
  Not sure that would work very well in practice.
aerovistae 11y ago
Exactly so. While this is a major advance, I roll my eyes at the sea of comments hailing the arrival of a superior intelligence. When the AI is cognizant of the fact that Go is a game, and knows what a game is, and perceives that the game is taking place in a larger reality, where there are other things happening while the game is going on....then I'll be impressed.
- partycoder 11y ago
  A significant part of that milestone was achieved when the IBM Watson defeated humans in Jeopardy.
  - ghaff 11y ago
    Huh? IBM Watson was able to answer trivia questions based on some impressive NLP (that I'd like to see more widely available) and a huge database of factual information. Oh, and it was able to beat humans in buzzing in. Watson was impressive, no doubt about it. But it certainly didn't have any meta knowledge of its place in the world or in a contest.
    - partycoder 11y ago
      What I mean is that the IBM Watson deals effectively deals with semantic information. You can make some analogies between sparse matrix data representations and what happens in the mammalian neocortex. It is of course not self conscious, but it effectively deals with semantic information and relationships among it.
- danbmil99 11y ago
  > ...then I'll be impressed. Or maybe not. The history of AI is one of humans always moving the goalposts when AI advances. Chess? just a computationally simple game. Driving? Well it's just physics. Go? now that requires intelligence oh wait, just some deep neural savant thing, not real AI
  - aerovistae 11y ago
jtolmar 11y ago
AlphaGo's algorithms will generalize easily to other perfect information games, including ones that include randomness like Backgammon. Games with imperfect information will take some more advances, but AlphaGo just opened up a lot of interesting potential paths, so there's a decent chance someone pursuing one of those will find something quickly. The sheer amount of computing power that AlphaGo needs will be a problem for games as complicated as Go for people who aren't Google. There will probably be more activity in simpler games with interesting properties. Non-game applications will require a fully formalized set of rules. The fact that formalizing what you want is hard is the reason we need programmers in the first place, so nothing fundamentally different there.
- return0 11y ago
  yes the problem is that games are the only formalizable apps. We need an AI to formalize the rest.
- SixSigma 11y ago
  Even knowing what rules one is using isn't always clear. I did some work for a Forex trader. He had devised an algorithm for trading and used it daily for modest gains. He engaged me to automate it for him via the vWorker freelance website [1]. I got the engine going getting the realtime price data etc. But when it came to his system it didn't work. In practice he didn't always act upon the signals he thought he did. We ended up in payment dispute because he insisted that if I had done the work right then the bot would be making money. By this time, I had learned the error of his thinking. We arbitrated on 50% payment - I wasn't too pleased with that but I had learned about trading. [1] https://en.wikipedia.org/wiki/VWorker https://en.wikipedia.org/wiki/VWorker
andreyk 11y ago
I think this is a great (and very overlooked) in depth assessment of the significance of this advance http://www.milesbrundage.com/blog-posts/alphago-and-ai-progress http://www.milesbrundage.com/blog-posts/alphago-and-ai-progr... I do feel that given all the hype and speculation about strong AI researchers in Deep Learning should really come forward to contextualize the real impact of this - which I think is not all that great.
- jtolmar 11y ago
  AlphaGo has no form of state space discovery. That really prevents all the magic that strong AI fans want. Even though the actual rules of Go are a minor part of the program, the human who put them in was doing something that AlphaGo fundamentally can't do. AlphaGo can't learn what Go is, it can only take an existing understanding of the rules and learn to play very well. You can expect a lot of advancement in actual games very soon, including ones with randomness, and after a few years probably hidden information games too. Being able to specify real-world problems as formally as a board game is now a more effective skill than it was before (it was good already).
tim333 11y ago
Part of the significance is that it was not the main goal for Deep Mind and Hassabis. He's said his main goal is to solve intelligence and it approaching it by trying to reverse engineer the human brain, having done a PhD in neuroscience. Hippocampus next. At this rate I'd be surprised if it took decades to real world generic applications.

by return0 11y ago

partycoder 11y ago

It is good enough now to replace millions of jobs. Transportation, retail, press, trading, etc. It is also good enough to put it in a combat drone that visually recognizes objectives and people. This can be all commanded by a small group of people, anonymously, and detached from accountability and without casualties.

scarmig 11y ago
Well, no casualties among the people ordering the AI. Kids going to their aunties' wedding, a bit less so. To say nothing of the casualties that'll be inflected on the AI warriors...
- hutzlibu 11y ago
  I guess, he was aware of that ...

nzonbi 11y ago

In my opinion a possible path is to make some sort of Symbolic AI (https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence https://en.wikipedia.org/wiki/Symbolic_artificial_intelligen...) system, and put machine learning on top, and even below of it. You could start with a very basic Symbolic AI, easier to understand. Then growth it gradually. The cool thing of this approach, would be that you could inspect the symbolic system to get a glance at how the AI system is thinking. Obviously a purely neuronal system can also do the trick. That is how the human brain works. But it would be great to make a system based on a symbolic AI, because it could be very interesting to observe its inner working. And it would also be possible to interact with it at the symbolic level.

deleted 11y ago
[deleted]
tim333 11y ago
Not sure that would work very well in practice.

aerovistae 11y ago

Exactly so. While this is a major advance, I roll my eyes at the sea of comments hailing the arrival of a superior intelligence. When the AI is cognizant of the fact that Go is a game, and knows what a game is, and perceives that the game is taking place in a larger reality, where there are other things happening while the game is going on....then I'll be impressed.

partycoder 11y ago
A significant part of that milestone was achieved when the IBM Watson defeated humans in Jeopardy.
- ghaff 11y ago
  Huh? IBM Watson was able to answer trivia questions based on some impressive NLP (that I'd like to see more widely available) and a huge database of factual information. Oh, and it was able to beat humans in buzzing in. Watson was impressive, no doubt about it. But it certainly didn't have any meta knowledge of its place in the world or in a contest.
  - partycoder 11y ago
    What I mean is that the IBM Watson deals effectively deals with semantic information. You can make some analogies between sparse matrix data representations and what happens in the mammalian neocortex. It is of course not self conscious, but it effectively deals with semantic information and relationships among it.
danbmil99 11y ago
> ...then I'll be impressed. Or maybe not. The history of AI is one of humans always moving the goalposts when AI advances. Chess? just a computationally simple game. Driving? Well it's just physics. Go? now that requires intelligence oh wait, just some deep neural savant thing, not real AI
- aerovistae 11y ago

jtolmar 11y ago

AlphaGo's algorithms will generalize easily to other perfect information games, including ones that include randomness like Backgammon. Games with imperfect information will take some more advances, but AlphaGo just opened up a lot of interesting potential paths, so there's a decent chance someone pursuing one of those will find something quickly. The sheer amount of computing power that AlphaGo needs will be a problem for games as complicated as Go for people who aren't Google. There will probably be more activity in simpler games with interesting properties. Non-game applications will require a fully formalized set of rules. The fact that formalizing what you want is hard is the reason we need programmers in the first place, so nothing fundamentally different there.

return0 11y ago
yes the problem is that games are the only formalizable apps. We need an AI to formalize the rest.
SixSigma 11y ago
Even knowing what rules one is using isn't always clear. I did some work for a Forex trader. He had devised an algorithm for trading and used it daily for modest gains. He engaged me to automate it for him via the vWorker freelance website [1]. I got the engine going getting the realtime price data etc. But when it came to his system it didn't work. In practice he didn't always act upon the signals he thought he did. We ended up in payment dispute because he insisted that if I had done the work right then the bot would be making money. By this time, I had learned the error of his thinking. We arbitrated on 50% payment - I wasn't too pleased with that but I had learned about trading. [1] https://en.wikipedia.org/wiki/VWorker https://en.wikipedia.org/wiki/VWorker

andreyk 11y ago

I think this is a great (and very overlooked) in depth assessment of the significance of this advance http://www.milesbrundage.com/blog-posts/alphago-and-ai-progress http://www.milesbrundage.com/blog-posts/alphago-and-ai-progr... I do feel that given all the hype and speculation about strong AI researchers in Deep Learning should really come forward to contextualize the real impact of this - which I think is not all that great.

jtolmar 11y ago
AlphaGo has no form of state space discovery. That really prevents all the magic that strong AI fans want. Even though the actual rules of Go are a minor part of the program, the human who put them in was doing something that AlphaGo fundamentally can't do. AlphaGo can't learn what Go is, it can only take an existing understanding of the rules and learn to play very well. You can expect a lot of advancement in actual games very soon, including ones with randomness, and after a few years probably hidden information games too. Being able to specify real-world problems as formally as a board game is now a more effective skill than it was before (it was good already).

tim333 11y ago

Part of the significance is that it was not the main goal for Deep Mind and Hassabis. He's said his main goal is to solve intelligence and it approaching it by trying to reverse engineer the human brain, having done a PhD in neuroscience. Hippocampus next. At this rate I'd be surprised if it took decades to real world generic applications.