John Hopfield (born July 15, 1933) is an American physicist and emeritus professor of Princeton University, most widely known for his study of associative neural networks in 1982.
I don’t think there’s another physicist in the town of Selborne, so that things slowly leak out over the news. But there’s no marching in the street here.
That’s right. I, my motivation was really coming from seeing that something does work, the brain, and understanding more about how the brain works would be necessary to understand thought consciousness or what have you.
And that it somehow was related to collective phenomena in networks. And I slowly wove my way from an interest in how the brain functioned to a question of how could hardware or software, or whatever you want to call it, wetware, produce such a thing.
And the centre of gravity of my knowledge and understanding moved slowly from much more physics oriented to the neurobiological one. And somewhere along the line, this connection between AI, networks, neural networks and physics developed.
In a good physics problem, you have a system which is well defined and where you can understand something about how collectively it may work in a way which is more robust than the individual little bits and pieces. You don’t leap into a problem overall saying, I want to understand how mind works.
You have to build up from the bottom. If you were doing weather, you would say, well, I want to understand what storms are without going back to interacting air nitrogen molecules.
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