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The unlabeled object recognition test is a standard test of machine learning algorithms.

Historically, error rates of around 20-25% won competitions and set records. A year or two ago, though some researchers and professors from the University of Toronto absolutely smashed those records, getting around a 16% error rate. They went and made a startup out of their tech, and got acquired by Google a few months ago.

I think that this is going to be the first of a long line of Google products integrating this sort of deep neural network technology. I wouldn't be shocked if Google in 10 years was known for something besides search, at this rate.




At the end of the day though, object recognition is also search, in a sense.

If I'm flipping through my album of dog photos, or looking especially closely at dogs via google glass, maybe Google will show me an ad for dog food?




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