Re:How close are we to solving vision?
by TheOtherHobbes on Sunday November 13, 2016 @05:06PM
(#12945949)
It's not obvious that humans really "understand" math. Or at least, only a very tiny minority of humans understand math well enough to improvise with it.
Most humans are only able to learn a small handful of "cookbook" math practices.
This is a standard trope in AI - AIs are compared with the sum total skill of human culture as a whole, not with the relatively weak skills of individual humans. (We have individuals with stand-out skills in specific domains, but there are no - at least virtually no - individuals with stand-out skills in many domains.)
Perhaps future approaches to AI will be collective. Instead of a single smart all-powerful monoAI we'll build evolving problem-solving polyAI cultures, and skim off the skills and insights they develop.
So "solving vision" isn't a useful measure. AI vision is getting close to classifying photos with human-like levels of consistency. 3D vision is still a problem, but will probably come with time.
But then what? Non-blind humans can all recognise familiar people, pick out strangers as strangers, identify a standard selection of objects, make educated guesses about non-familiar objects, and so on.
But humans can also appreciate art, identify memes and find them amusing, respond to font choices and colours, describe and label spatial relationships and views, and point to the location of objects/places that are not currently in view.
Trained artists and architects can identity and name specific proportions and identify cultural references.
Etc. How many of these are necessary to "solve vision"?
Most humans are only able to learn a small handful of "cookbook" math practices.
This is a standard trope in AI - AIs are compared with the sum total skill of human culture as a whole, not with the relatively weak skills of individual humans. (We have individuals with stand-out skills in specific domains, but there are no - at least virtually no - individuals with stand-out skills in many domains.)
Perhaps future approaches to AI will be collective. Instead of a single smart all-powerful monoAI we'll build evolving problem-solving polyAI cultures, and skim off the skills and insights they develop.
So "solving vision" isn't a useful measure. AI vision is getting close to classifying photos with human-like levels of consistency. 3D vision is still a problem, but will probably come with time.
But then what? Non-blind humans can all recognise familiar people, pick out strangers as strangers, identify a standard selection of objects, make educated guesses about non-familiar objects, and so on.
But humans can also appreciate art, identify memes and find them amusing, respond to font choices and colours, describe and label spatial relationships and views, and point to the location of objects/places that are not currently in view.
Trained artists and architects can identity and name specific proportions and identify cultural references.
Etc. How many of these are necessary to "solve vision"?