7 ms·

Back in 2005 I suggested that it would be interesting to build a system that would play any game without being given directions (that blog post has since disapp

by mojuba 11y ago

Back in 2005 I suggested that it would be interesting to build a system that would play any game without being given directions (that blog post has since disappeared from the web). This, and not image recognition, would mean intelligence, I thought at the time: you can't truly tell a donkey from a dog without having some general knowledge about the world donkeys and dogs (and your AI) are living in. The academic image recognition machine though seems unstoppable and yes it does seem to improve over time. I honestly don't know what the limits of "dumb" image recognition are in terms of quality, but calling it AI still doesn't make sense to me.

gnaritas 11y ago
> but calling it AI still doesn't make sense to me. That's the core problem of AI, no matter what progress is made, it's instantly called not AI anymore while the goalpost of what AI is is continually being pushed out to not this. The real issue of course is what don't how intelligence actually works so it's impossible to set a fixed goalpost of when AI is truly achieved.
- jacquesm 11y ago
  The reason behind that is probably that a large enough collection of interconnected algorithms executing simultaneously may be indistinguishable from intelligence. The questions then becomes 'what is large enough' and 'which algorithms', and this is where we may be off by much more than our most optimistic guesses and that still leaves the possibility of being flat-out wrong about this.
  - gnaritas 11y ago
    > that a large enough collection of interconnected algorithms executing simultaneously may be indistinguishable from intelligence Or is intelligence.
- maaku 11y ago
  > The real issue of course is what don't how intelligence actually works so it's impossible to set a fixed goalpost of when AI is truly achieved. No, the real issue is that people still think, intuitively, that there's a little homunculus in their head making the decisions. Each time we build something that doesn't look like a homunculus, we've failed at attaining "real" intelligence...
  - mojuba 11y ago
    Making decisions is not that complicated, neither is it interesting. Your iPhone can make a decision to kill a process that takes too much system resources while in the background. What's more interesting (and what seems to be the main function of the so called homunculus) is being aware of your own location in space and time, as well as remembering previous locations. In other words, having some model of the world and knowing your place in it is what computers haven't achieved yet in any meaningful way.
    - dllthomas 11y ago
      So, map building is now what will truly define AI until it's also just another technology.
      - dkarapetyan 11y ago
        How is map building AI? It's a pretty mechanical process. Start somewhere, make some measurements, move along, repeat. At what point is there any notion of intelligence involved?
        dllthomas 11y ago
        It's deeper than you describe... https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping https://en.wikipedia.org/wiki/Simultaneous_localization_and_... ... but I agree that there's nothing in particular that distinguishes it from other problems. My comment was satirical in nature. SLAM is an interpretation of what the parent comment had described: "[B]eing aware of your own location in space and time, as well as remembering previous locations. In other words, having some model of the world and knowing your place in it[.]". There is a general pattern of statements of the form "We'll only really have AI when computers X", followed by computers being able to X, followed by everyone concluding that X is just a simple matter of engineering like everything else we've already accomplished. As my AI prof put it, ages ago, "AI is the study of things that don't work yet."
ig1 11y ago
That's actually trivially doable and has been done for video games and board games.
- lifeformed 11y ago
  One that can play ANY game, not programmed to play a specific one.
  - ig1 11y ago
    Yes, it's trivial. For board games all AIs essentially use Alpha–beta pruning + scoring function and an approximation to that scoring function can be autogenerated using standard machine learning techniques. For (classic) video games it's actually somewhat similar but rather than a board being fed in as an input you just feed in a bitmap of the display (sometimes at a lower resolution using compression techniques to reduce input features) and optimize moves made to maximize the score at any point rather than end-game.
enave 11y ago
This is true. The reason there's a scene in the movie, 2001, in which HAL plays chess is that at the time it was thought that playing chess well required real human intelligence. But as soon as chess programs got good, we all took them for granted.
CyberDildonics 11y ago
There isn't a lot in the world of AI that seems worthy of the I. Image recognition though, while not a part of our conscious reasoning is a very strong part of our brains. It continues to advance because it is immediately profitable.
Houshalter 11y ago
That's actually starting to happen. Deepmind built an AI that can learn to beat the best human players on many atari games. After just a few hours of playing the game and learning. And of course it uses all that advanced image recognition stuff. That has always been the hard part. The actual game playing part is just a simple reinforcement learning neural network that is put on top of it. The reason it's AI is because it isn't specific to speech recognition. Deep learning is very general. The same algorithms work just as well at speech recognition, or translation, or controlling robots, etc. Image recognition is just the most popular application.
- argonaut 11y ago
  Important to realize the AI fails completely at other Atari games.
  - daveguy 11y ago
    Specifically the ones that require any sort of identification of state. It kicks butt in hand eye coordination tasks and it is awesome that it can learn those hand-eye tasks automatically, but higher order reasoning is obviously out. AI makes progress every year and when those progress in individual tasks are coalesced into a coherent single entity we will have what the average person calls intelligent.
    - versteegen 11y ago
      Yes, but that's because the specific ANN the Deepmind researchers used doesn't have any state. IIRC it's given the last 2 or 3 frames as input. No doubt that makes the learning easier (I should mention that reinforcement learning is used, unlike most tasks ANNs are applied to). But recently stateful ANNs (typically based on Long Short-Term Memory (LSTM) networks, from 1997 already) are becoming more and more popular. I would like to see someone make another attempt at Atari games with such a stateful network; probably already done actually.
- colordrops 11y ago
  I've read elsewhere that they trained in whether the score went up. For it to really be a general game playing AI, it should be able to figure out the goals of games without scoring systems, such as adventure games.
paulsutter 11y ago
AGI is the idea of creating general intelligence. Which almost certainly requires some reinforcement learning (the ways dogs and humans learn, by having a goal and an internal reward system). Deepmind's Atari player is based on deep reinforcement learning, where increasing the score represents a reward: https://m.youtube.com/watch?v=EfGD2qveGdQ https://m.youtube.com/watch?v=EfGD2qveGdQ I used to believe the moving goalpost idea, that AI is anything that isn't yet possible. I now disagree. I saved myself a lot of energy by avoiding entirely the question "what counts as AI?" by switching to the question, "what counts as AGI?" which is a term with a clearer threshold: https://en.m.wikipedia.org/wiki/Artificial_general_intelligence https://en.m.wikipedia.org/wiki/Artificial_general_intellige...
rdtsc 11y ago
AI is like magic. If you don't know how it works -- it looks like magic. It can tell a donkey from a horse, it can play checkers, diagnose a patient etc. After you are told the trick -- it is just A*, or Rete algorithm, or a multi-layer NN. It makes it less magic and it becomes just another algorithm.

by mojuba 11y ago

gnaritas 11y ago

> but calling it AI still doesn't make sense to me. That's the core problem of AI, no matter what progress is made, it's instantly called not AI anymore while the goalpost of what AI is is continually being pushed out to not this. The real issue of course is what don't how intelligence actually works so it's impossible to set a fixed goalpost of when AI is truly achieved.

jacquesm 11y ago
The reason behind that is probably that a large enough collection of interconnected algorithms executing simultaneously may be indistinguishable from intelligence. The questions then becomes 'what is large enough' and 'which algorithms', and this is where we may be off by much more than our most optimistic guesses and that still leaves the possibility of being flat-out wrong about this.
- gnaritas 11y ago
  > that a large enough collection of interconnected algorithms executing simultaneously may be indistinguishable from intelligence Or is intelligence.
maaku 11y ago
> The real issue of course is what don't how intelligence actually works so it's impossible to set a fixed goalpost of when AI is truly achieved. No, the real issue is that people still think, intuitively, that there's a little homunculus in their head making the decisions. Each time we build something that doesn't look like a homunculus, we've failed at attaining "real" intelligence...
- mojuba 11y ago
  Making decisions is not that complicated, neither is it interesting. Your iPhone can make a decision to kill a process that takes too much system resources while in the background. What's more interesting (and what seems to be the main function of the so called homunculus) is being aware of your own location in space and time, as well as remembering previous locations. In other words, having some model of the world and knowing your place in it is what computers haven't achieved yet in any meaningful way.
  - dllthomas 11y ago
    So, map building is now what will truly define AI until it's also just another technology.
    - dkarapetyan 11y ago
      How is map building AI? It's a pretty mechanical process. Start somewhere, make some measurements, move along, repeat. At what point is there any notion of intelligence involved?
      - dllthomas 11y ago
        It's deeper than you describe... https://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping https://en.wikipedia.org/wiki/Simultaneous_localization_and_... ... but I agree that there's nothing in particular that distinguishes it from other problems. My comment was satirical in nature. SLAM is an interpretation of what the parent comment had described: "[B]eing aware of your own location in space and time, as well as remembering previous locations. In other words, having some model of the world and knowing your place in it[.]". There is a general pattern of statements of the form "We'll only really have AI when computers X", followed by computers being able to X, followed by everyone concluding that X is just a simple matter of engineering like everything else we've already accomplished. As my AI prof put it, ages ago, "AI is the study of things that don't work yet."

ig1 11y ago

That's actually trivially doable and has been done for video games and board games.

lifeformed 11y ago
One that can play ANY game, not programmed to play a specific one.
- ig1 11y ago
  Yes, it's trivial. For board games all AIs essentially use Alpha–beta pruning + scoring function and an approximation to that scoring function can be autogenerated using standard machine learning techniques. For (classic) video games it's actually somewhat similar but rather than a board being fed in as an input you just feed in a bitmap of the display (sometimes at a lower resolution using compression techniques to reduce input features) and optimize moves made to maximize the score at any point rather than end-game.

enave 11y ago

This is true. The reason there's a scene in the movie, 2001, in which HAL plays chess is that at the time it was thought that playing chess well required real human intelligence. But as soon as chess programs got good, we all took them for granted.

CyberDildonics 11y ago

There isn't a lot in the world of AI that seems worthy of the I. Image recognition though, while not a part of our conscious reasoning is a very strong part of our brains. It continues to advance because it is immediately profitable.

Houshalter 11y ago

That's actually starting to happen. Deepmind built an AI that can learn to beat the best human players on many atari games. After just a few hours of playing the game and learning. And of course it uses all that advanced image recognition stuff. That has always been the hard part. The actual game playing part is just a simple reinforcement learning neural network that is put on top of it. The reason it's AI is because it isn't specific to speech recognition. Deep learning is very general. The same algorithms work just as well at speech recognition, or translation, or controlling robots, etc. Image recognition is just the most popular application.

argonaut 11y ago
Important to realize the AI fails completely at other Atari games.
- daveguy 11y ago
  Specifically the ones that require any sort of identification of state. It kicks butt in hand eye coordination tasks and it is awesome that it can learn those hand-eye tasks automatically, but higher order reasoning is obviously out. AI makes progress every year and when those progress in individual tasks are coalesced into a coherent single entity we will have what the average person calls intelligent.
  - versteegen 11y ago
    Yes, but that's because the specific ANN the Deepmind researchers used doesn't have any state. IIRC it's given the last 2 or 3 frames as input. No doubt that makes the learning easier (I should mention that reinforcement learning is used, unlike most tasks ANNs are applied to). But recently stateful ANNs (typically based on Long Short-Term Memory (LSTM) networks, from 1997 already) are becoming more and more popular. I would like to see someone make another attempt at Atari games with such a stateful network; probably already done actually.
colordrops 11y ago
I've read elsewhere that they trained in whether the score went up. For it to really be a general game playing AI, it should be able to figure out the goals of games without scoring systems, such as adventure games.

paulsutter 11y ago

AGI is the idea of creating general intelligence. Which almost certainly requires some reinforcement learning (the ways dogs and humans learn, by having a goal and an internal reward system). Deepmind's Atari player is based on deep reinforcement learning, where increasing the score represents a reward: https://m.youtube.com/watch?v=EfGD2qveGdQ https://m.youtube.com/watch?v=EfGD2qveGdQ I used to believe the moving goalpost idea, that AI is anything that isn't yet possible. I now disagree. I saved myself a lot of energy by avoiding entirely the question "what counts as AI?" by switching to the question, "what counts as AGI?" which is a term with a clearer threshold: https://en.m.wikipedia.org/wiki/Artificial_general_intelligence https://en.m.wikipedia.org/wiki/Artificial_general_intellige...

rdtsc 11y ago

AI is like magic. If you don't know how it works -- it looks like magic. It can tell a donkey from a horse, it can play checkers, diagnose a patient etc. After you are told the trick -- it is just A*, or Rete algorithm, or a multi-layer NN. It makes it less magic and it becomes just another algorithm.