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I’m confused by your comment because these are exactly the type of problems that humans generally really do a poor job classifying.



Most modern ML techniques do a poor job on these types of problems too unless they have a lot of data (hence the reference to sparsity) or assume structure that requires domain specific modeling to capture.


It could be that after we train a biological nural net for decades it can get pretty good at intuiting things even if it can't explain how.

The numeral net in question is the Drs. Brain.




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