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Known Unknowns


Here’s a story about how machines learn. Say you are the US Army and you want to be able to locate enemy tanks in a forest. The tanks are painted with camouflage, parked among trees, and covered in brush. To the human eye, the blocky outlines of the tanks are indistinguishable from the foliage. But you develop another way of seeing: you train a machine to identify the tanks. To teach the machine, you take a hundred photos of tanks in the forest, then a hundred photos of the empty forest. You show half of each set to a neural network, a piece of software designed to mimic a human brain. The neural network doesn’t know anything about tanks and forests; it just knows that there are fifty pictures with something important in them and fifty pictures without that something, and it tries to spot the difference. It examines the photos from multiple angles, tweaks and judges them, without any of the distracting preconceptions inherent in the human brain.

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