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Yes but children can pass these tests when presented with a single photo as well (if I understand the setup correctly), so I'd say it's a fair comparison. The a

Yes but children can pass these tests when presented with a single photo as well (if I understand the setup correctly), so I'd say it's a fair comparison. The algorithm can "look" at the picture as long as it wants as well, e.g. using many different convolutional filters that can "see" features in different parts of the image and then combine these in later stages of the analysis.

ivan_gammel 8y ago
How close are those convolutional filters to the physical sight of animals? Were they designed specifically to mimic nature or they are artificial concept with similar purpose?
- singularity2001 8y ago
  First they were designed to mimic nature, then these patterns (gabor filters) astonishingly automatically developed themselves via backpropagation (which gave rise to the recent enthusiasm). Modern networks are instantiated with random noise but end up pretty much the same as previously hardcoded filters.
- ThePhysicist 8y ago
  Actually the artificial neural networks used for vision tasks are not so different from our visual cortex, there's an interesting Nature paper on this: https://www.nature.com/articles/s42003-018-0110-y https://www.nature.com/articles/s42003-018-0110-y Of course the neurons in our brain work in a very different way, but at an architecture level the strategies of natural and artificial neural networks seem to match.
  - ivan_gammel 8y ago
    Thank you for the link! Indeed, that's very interesting reading.
- TeMPOraL 8y ago
  They may be close to first stages of sight pipeline. Maybe even close to full pipe for some simple animals. For humans, they're pretty much input processing stage. Human vision (and presumably animal vision too) has runtime feedback that uses the the output of the vision process to fix up the input. That's what makes you suddenly see things if someone tells you what to look for, or suddenly unsee things. That's why you didn't notice I repeated the the word "the" in few places in this comment. As the intro to the the article says (you now noticed, didn't you?), the way DNN vision systems are different is that "unlike humans, they can’t do a double take". And those "double takes" is what our vision pipeline does all the time.
  - joejerryronnie 8y ago
    Very clever young man, but it's turtles all the way down!
deleted 8y ago
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ivan_gammel 8y ago

How close are those convolutional filters to the physical sight of animals? Were they designed specifically to mimic nature or they are artificial concept with similar purpose?

singularity2001 8y ago
First they were designed to mimic nature, then these patterns (gabor filters) astonishingly automatically developed themselves via backpropagation (which gave rise to the recent enthusiasm). Modern networks are instantiated with random noise but end up pretty much the same as previously hardcoded filters.
ThePhysicist 8y ago
Actually the artificial neural networks used for vision tasks are not so different from our visual cortex, there's an interesting Nature paper on this: https://www.nature.com/articles/s42003-018-0110-y https://www.nature.com/articles/s42003-018-0110-y Of course the neurons in our brain work in a very different way, but at an architecture level the strategies of natural and artificial neural networks seem to match.
- ivan_gammel 8y ago
  Thank you for the link! Indeed, that's very interesting reading.
TeMPOraL 8y ago
They may be close to first stages of sight pipeline. Maybe even close to full pipe for some simple animals. For humans, they're pretty much input processing stage. Human vision (and presumably animal vision too) has runtime feedback that uses the the output of the vision process to fix up the input. That's what makes you suddenly see things if someone tells you what to look for, or suddenly unsee things. That's why you didn't notice I repeated the the word "the" in few places in this comment. As the intro to the the article says (you now noticed, didn't you?), the way DNN vision systems are different is that "unlike humans, they can’t do a double take". And those "double takes" is what our vision pipeline does all the time.
- joejerryronnie 8y ago
  Very clever young man, but it's turtles all the way down!

deleted 8y ago

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