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You're in danger of missing the point too far in the other direction. The system just returns yes/no as to whether an image has a face in it, and if it was hard-coded to respond "no" it would score 64.8%.

Obviously this is extremely impressive work, and given that Google gives away 1e9 core hours a year, I'd like to see how much further they can push this network (which only used 16e3x3x24 ~ 1e6 hours). But this isn't like scoring 80% in a written exam.

I'm also impressed by how readable the paper was. Apart from a few paragraphs of detailed maths this should be accessible to anyone who's read the wikipedia article on neural networks.

http://googleblog.blogspot.com/2011/04/1-billion-computing-c...



* The system just returns yes/no as to whether an image has a face in it, and if it was hard-coded to respond "no" it would score 64.8%.*

Yes, that is true. But ~80% correct is still a significant result.

I was hoping people would read beyond the 15% headline figure to understand exactly what than number meant.




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