Deep learning is just another way of doing statistics.
-it makes strong assumption
-you have large amounts of data
-classifying into categories.
-test data aren't far from training examples
@GaryMarcus #ttiintelligencepic.twitter.com/7xcFRNE3NI
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We can represent the angle as indeterminate. If you need to reason about the cow, you generate it with a definite angle but put low confidence on it, so the angle is not clamped down and can be regenerated if the constraints change.
Other representations use multiple alternative prototypes to cover the feature space. What fools you is that attentional access uses lateral inhibition to collapse it into one.
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