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The visual system is basically a deep neural net of the type we are already building, but it's self-contained. Generally it seems like our brain is composed of

by tormeh 10y ago

The visual system is basically a deep neural net of the type we are already building, but it's self-contained. Generally it seems like our brain is composed of a lot of fixed-function neural nets (and other algorithms) which are then integrated by less specialized units. That's my impression anyway. I think maybe our artificial visual nets are too general, actually, in comparison to natural ones. It not only describes what it sees, but tries to analyze it too. Showing a picture of a dog results in "dog", rather than "big four-legged furry thing". Expecting a visual system to know that a chihuahua and a German shepherd is the same thing is maybe a case of grouping tasks that shouldn't be grouped.

sounds 10y ago
In order to build an artificial visual system, humans must grasp what their own visual system does. In order to describe what the human visual system does we use words like "dog" -- and I would agree with you, "big four-legged furry mammal" might be better, but artificial visual systems work more at the level of "80% probability of dog," "2% probability of brick," "90% probability of chihuahua," and they don't really know that chihuahua must always imply dog. In order to describe the function of the visual system, a fundamental change really must happen in the way the system's output is described. Using plain written words as output may work as a system but it is not an exact replica of a human visual system. It is more of a trained animal act: when you see dog-like images, press the button labelled "dog" (does the animal even comprehend what a dog is?) In order to rethink the way we describe output, we will have to come up with a very precise description of the inside potentials and activations in mammalian brains. We are just barely creating tools to describe what an artificial neural net "is thinking." So I guess we're starting to look in that direction.

by tormeh 10y ago

sounds 10y ago

In order to build an artificial visual system, humans must grasp what their own visual system does. In order to describe what the human visual system does we use words like "dog" -- and I would agree with you, "big four-legged furry mammal" might be better, but artificial visual systems work more at the level of "80% probability of dog," "2% probability of brick," "90% probability of chihuahua," and they don't really know that chihuahua must always imply dog. In order to describe the function of the visual system, a fundamental change really must happen in the way the system's output is described. Using plain written words as output may work as a system but it is not an exact replica of a human visual system. It is more of a trained animal act: when you see dog-like images, press the button labelled "dog" (does the animal even comprehend what a dog is?) In order to rethink the way we describe output, we will have to come up with a very precise description of the inside potentials and activations in mammalian brains. We are just barely creating tools to describe what an artificial neural net "is thinking." So I guess we're starting to look in that direction.