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Does your brain confuse this squiggly line for a dog? http://www.pablopicasso.net/dog/ http://www.pablopicasso.net/dog/ It doesn't look anything like a dog!

EliRivers 9y ago
That's a good question; I can look at that and say it's not a dog, but it is a deliberate representation of a dog. It doesn't confuse me into thinking it is a dog. Do the NNs differentiate between an actual object and a representation of an object? Given that their input is (I understand) just a 2D image, I could imagine the question itself makes no sense in the context of a NN. To an NN, a picture of a dog is a dog.
- IshKebab 9y ago
  Nope you could easily train a CNN to distinguish photos of real dogs from drawings of dogs.
  - EliRivers 9y ago
    How about a real dog and a photo of a real dog? Having been taught the difference between a photo of a dog and a drawing of a dog, would it then be able to differentiate between a photo of any object and a drawing of that object, or do we need to teach it the difference again for every different object there is? If I teach it to identify a simple two colour single-line drawing of a dog, like that Picasso picture, will it then be able to handle surrealist drawings of dogs, and impressionist, and cubist, and a picture of a sculpture, and watercolours and charcoal and all the other varieties of form and style, or do I need to teach it separately for everything? Don't forget slide puzzles! I can tell this is a dog - https://lh3.googleusercontent.com/oAtmNcl25MPQOZ5Occ_fr7_BKrxjQ_5uyZ13WKupm3MtZaXne-BLqlIQ8ZXk7n7augM=h900 https://lh3.googleusercontent.com/oAtmNcl25MPQOZ5Occ_fr7_BKr... These of course are hypothetical questions; I suspect the answer is that there is going to be an awful lot of teaching, with a few pleasant surprises when it gets one style of artwork from having seen enough of other styles. Except the first one; to the NN, a real dog is a picture of a dog - with no concept of real object behind the picture, the NN's universe is pictures and it will only ever be a simple machine for identifying things in a very very narrow universe. Nothing I'm saying here is news to anyone, of course, but sometimes it seems like these NNs are portrayed as general identifiers, when they're actually very narrow.
    - Houshalter 9y ago
      Even actual dogs wouldn't recognize that image as a picture of a dog. NNs have approached at least animal levels of intelligence which is amazing.
- dEnigma 9y ago
  In the same vein: is this a pipe? https://en.m.wikipedia.org/wiki/The_Treachery_of_Images https://en.m.wikipedia.org/wiki/The_Treachery_of_Images I think all the other fail-safes human brains have would be a pretty good protection against OP's scenario. When I'm not seeing clear I automatically take a second look, try a different angle, realize that something isn't quite right and evaluate the whole situation accordingly. All things that today's neural networks don't and can't do.
  - Sharlin 9y ago
    Individual NNs themselves, true, but a comprehensive machine vision package such as one in an autonomous vehicle definitely must - and does - have that sort of situational awareness and sensor fusion from multiple input sources.
    - dEnigma 9y ago
      Exactly, and those systems aren't vulnerable to such simple attacks, at least as far as we know. The human visual system, and everything connected to it, is even more complex and sophisticated, so I think it's fair to say that it would be even harder to trick it like that. On the other hand, maybe this complexity and sheer amount of processing makes us susceptible to another kind of trick (like advanced optical illusions)
deleted 9y ago
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EliRivers 9y ago

That's a good question; I can look at that and say it's not a dog, but it is a deliberate representation of a dog. It doesn't confuse me into thinking it is a dog. Do the NNs differentiate between an actual object and a representation of an object? Given that their input is (I understand) just a 2D image, I could imagine the question itself makes no sense in the context of a NN. To an NN, a picture of a dog is a dog.

IshKebab 9y ago
Nope you could easily train a CNN to distinguish photos of real dogs from drawings of dogs.
- EliRivers 9y ago
  How about a real dog and a photo of a real dog? Having been taught the difference between a photo of a dog and a drawing of a dog, would it then be able to differentiate between a photo of any object and a drawing of that object, or do we need to teach it the difference again for every different object there is? If I teach it to identify a simple two colour single-line drawing of a dog, like that Picasso picture, will it then be able to handle surrealist drawings of dogs, and impressionist, and cubist, and a picture of a sculpture, and watercolours and charcoal and all the other varieties of form and style, or do I need to teach it separately for everything? Don't forget slide puzzles! I can tell this is a dog - https://lh3.googleusercontent.com/oAtmNcl25MPQOZ5Occ_fr7_BKrxjQ_5uyZ13WKupm3MtZaXne-BLqlIQ8ZXk7n7augM=h900 https://lh3.googleusercontent.com/oAtmNcl25MPQOZ5Occ_fr7_BKr... These of course are hypothetical questions; I suspect the answer is that there is going to be an awful lot of teaching, with a few pleasant surprises when it gets one style of artwork from having seen enough of other styles. Except the first one; to the NN, a real dog is a picture of a dog - with no concept of real object behind the picture, the NN's universe is pictures and it will only ever be a simple machine for identifying things in a very very narrow universe. Nothing I'm saying here is news to anyone, of course, but sometimes it seems like these NNs are portrayed as general identifiers, when they're actually very narrow.
  - Houshalter 9y ago
    Even actual dogs wouldn't recognize that image as a picture of a dog. NNs have approached at least animal levels of intelligence which is amazing.
dEnigma 9y ago
In the same vein: is this a pipe? https://en.m.wikipedia.org/wiki/The_Treachery_of_Images https://en.m.wikipedia.org/wiki/The_Treachery_of_Images I think all the other fail-safes human brains have would be a pretty good protection against OP's scenario. When I'm not seeing clear I automatically take a second look, try a different angle, realize that something isn't quite right and evaluate the whole situation accordingly. All things that today's neural networks don't and can't do.
- Sharlin 9y ago
  Individual NNs themselves, true, but a comprehensive machine vision package such as one in an autonomous vehicle definitely must - and does - have that sort of situational awareness and sensor fusion from multiple input sources.
  - dEnigma 9y ago
    Exactly, and those systems aren't vulnerable to such simple attacks, at least as far as we know. The human visual system, and everything connected to it, is even more complex and sophisticated, so I think it's fair to say that it would be even harder to trick it like that. On the other hand, maybe this complexity and sheer amount of processing makes us susceptible to another kind of trick (like advanced optical illusions)

deleted 9y ago

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