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" "In late 1985, I actually had a deal with Dave Rumelhart that I would write a short paper about backpropagation, which was his idea, and he would write a short paper about autoencoders, which was my idea. It was always better to have someone who didn't come up with the idea write the paper because he could say more dearly what was important. So I wrote the short paper about backpropagation, which was the Nature paper that came out in 1986, but Dave still hasn't written the short paper about autoencoders. I'm still waiting.
Geoffrey Everest Hinton (born 6 December 1947) is an English-Canadian cognitive psychologist and computer scientist best known for his work on artificial neural networks. Since 2013, he divides his time working for Google (Google Brain) and the University of Toronto.
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I'm much more interested in how the brain does it. I'm only interested in applications just to prove that this is interesting stuff to keep the funding flowing. To do an application really well, you have to put your whole heart into it; you need to spend a year immersing yourself in what the application' s all about. I guess I've never really been prepared to do that.
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... as soon as I got backpropagation working, I realized--because of what we'd been doing with Boltzmann machines--that you could use autoencoders to do unsupervised learning. You just get the output layer to reproduce the input layer, and then you don't need a separate teaching signal. Then the hidden units are representing some code for the input.