4 ms·

> So when a human thinks about a cat, she can probably picture the way it moves, hear the sound of purring, feel the impending scratch from an unsheathed claw.

> So when a human thinks about a cat, she can probably picture the way it moves, hear the sound of purring, feel the impending scratch from an unsheathed claw. She has a rich store of sensory information at her disposal to understand the idea of a ‘cat’, and other related concepts that might help her interact with such a creature. Except a very large fraction of people don't think this way (eg. those with aphantasia), and Helen Keller certainly didn't, yet seems to have been as smart as any of us. So obviously intelligence does not depend on having a huge breadth of sensory experience. It's quite tiring how much posturing about what's ‘really’ missing from machine intelligence doesn't last past 5 seconds of basic fact checking.

uoaei 7y ago
Breadth can also be considered "diversity" in this case, i.e., experiencing the cat against many different background environments and the time-evolution of the sensory readings attributable to the cat relative to that background. Breadth also refers perhaps to the massively parallel sensor streams. The sense of touch is not one experience, but the amalgamation of millions of experiences -- one per nerve ending. So far the sensor platforms we develop artificially have on the order of 1000s of sensors, not the millions that distinguish the combination of temperature and pressure at certain "optimized" key points. Rote and myopic counterarguments do not a futurism-oriented discussion make.
v64 7y ago
> Except a very large fraction of people don't think this way (eg. those with aphantasia) I don't think it's accurate to say that aphants don't have this type of sensory information at their disposal. I have aphantasia, but I still experience the world through my senses. I may not be able to visualize a cat in my mind's eye, but based on my prior experiences with cats, I know a cat when I see one. If I hear purring, I recognize that as a sound that cats I've encountered in the past have made, etc.
- Veedrac 7y ago
  Yes, you are capable of pattern matching. The point is that this is a distinct thing from intellectual ability, since we know having orders of magnitude less sensory input doesn't much seem to limit the ability to do high-level reasoning, and know some people don't use it as part of high-level reasoning. This kind of pattern matching is also fairly evidently not all that difficult, since much simpler brains than ours can manage it, as can ML models with caveats (albeit caveats often misunderstood and exaggerated).
  - eli_gottlieb 7y ago
    >This kind of pattern matching is also fairly evidently not all that difficult, since much simpler brains than ours can manage it, as can ML models with caveats (albeit caveats often misunderstood and exaggerated). Do tell me, since I'm writing a paper on a related topic, which current ML models can "pattern match" to recognize or generate multimodal (ie: visual, auditory, and tactile) percepts of cats, in arbitrary poses, in any context where cats are usually/realistically found? Or did you just mean that the "cat" subset of Imagenet is as "solved" as the rest of Imagenet?
    - Veedrac 7y ago
      Please try to argue in good faith. I've already said ML models have caveats, obviously I don't think they're perfect or par-human.
      - eli_gottlieb 7y ago
        I think that "perfect" or "par-human" would be a judgement about performance on a set computational task. My caveat is that ML models are usually performing a vastly simplified task compared to what the brain does. But it looked like you were saying they perform "pattern matching" with the same task setting and cost function as the brain, and just need to perform better at it. What's your view?
        Veedrac 7y ago

uoaei 7y ago

Breadth can also be considered "diversity" in this case, i.e., experiencing the cat against many different background environments and the time-evolution of the sensory readings attributable to the cat relative to that background. Breadth also refers perhaps to the massively parallel sensor streams. The sense of touch is not one experience, but the amalgamation of millions of experiences -- one per nerve ending. So far the sensor platforms we develop artificially have on the order of 1000s of sensors, not the millions that distinguish the combination of temperature and pressure at certain "optimized" key points. Rote and myopic counterarguments do not a futurism-oriented discussion make.

v64 7y ago

> Except a very large fraction of people don't think this way (eg. those with aphantasia) I don't think it's accurate to say that aphants don't have this type of sensory information at their disposal. I have aphantasia, but I still experience the world through my senses. I may not be able to visualize a cat in my mind's eye, but based on my prior experiences with cats, I know a cat when I see one. If I hear purring, I recognize that as a sound that cats I've encountered in the past have made, etc.

Veedrac 7y ago
Yes, you are capable of pattern matching. The point is that this is a distinct thing from intellectual ability, since we know having orders of magnitude less sensory input doesn't much seem to limit the ability to do high-level reasoning, and know some people don't use it as part of high-level reasoning. This kind of pattern matching is also fairly evidently not all that difficult, since much simpler brains than ours can manage it, as can ML models with caveats (albeit caveats often misunderstood and exaggerated).
- eli_gottlieb 7y ago
  >This kind of pattern matching is also fairly evidently not all that difficult, since much simpler brains than ours can manage it, as can ML models with caveats (albeit caveats often misunderstood and exaggerated). Do tell me, since I'm writing a paper on a related topic, which current ML models can "pattern match" to recognize or generate multimodal (ie: visual, auditory, and tactile) percepts of cats, in arbitrary poses, in any context where cats are usually/realistically found? Or did you just mean that the "cat" subset of Imagenet is as "solved" as the rest of Imagenet?
  - Veedrac 7y ago
    Please try to argue in good faith. I've already said ML models have caveats, obviously I don't think they're perfect or par-human.
    - eli_gottlieb 7y ago
      I think that "perfect" or "par-human" would be a judgement about performance on a set computational task. My caveat is that ML models are usually performing a vastly simplified task compared to what the brain does. But it looked like you were saying they perform "pattern matching" with the same task setting and cost function as the brain, and just need to perform better at it. What's your view?
      - Veedrac 7y ago