Comment Re:Actually a Great Step Forward (Score 1) 130
Computer learns to pick out salient features to identify images. Then we are shocked that when trained with no supervision the salient features aren’t what we would have chosen.
There is a huge difference: humans pick relevant features guided by a deep understanding of the world, while machine learning, unguided by any understanding, only does so by chance.
Now that we know what computers are picking out as salient features, we can modify the algorithms to add additional constraints on what additional salient features must or must not be in an object identified, such that it would correspond more closely to how humans would classify objects. Baseballs must have curvature for instance not just zig-zag red lines on white.
Hand-coded fixes are not AI - that would be as if we have we had a higher-level intelligent agent in our heads to correct our mistakes (see the homunculus fallacy).