... 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… - Geoffrey Hinton

I think political systems will use it to terrorize people.

I first of all explained to him why it wouldn't work, based on an argument in Rosenblatt's book, which showed that essentially it was an algorithm that couldn't break symmetry... The next argument I gave him was that it would get stuck in local minima... We programmed a backpropagation net, and we tried to get this fast relearning. It didn't give fast relearning, so I made one of these crazy inferences that people make--which was, that backpropagation is not very interesting... [One year of trying and failing to scale up Boltzmann machines later] "Well, maybe, why don't I just program up that old idea of Rumelhart's, and see how well that works on some of the problems we've been trying?"... We had all the arguments: It's assuming that neurons can send real numbers to each other; of course they can only send bits to each other ; you have to have stochastic binary neurons; these real-valued neurons are totally unrealistic. It's ridiculous." So they just refused to work on it, not even to write a program, so I had to do it myself.

The reason hidden units in neural nets are called hidden units is that Peter Brown told me about hidden Markov models. I decided "hidden" was a good name for those extra units, so that's where the name "hidden" comes from.