One major strand in the history would be cybernetics/control theory, which was applied physics initially—the radar-controlled antiaircraft gun being the paradigm for the field
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Replying to @Meaningness @michael_nielsen
This is the long forgotten connection. What happened was that the Dartmouth AI folk didn't invite Wiener because his approach was very different from emerging computer paradigm.
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Replying to @IntuitMachine @michael_nielsen
Right. And that antipathy led to the Minsky/Papert Perceptrons book, and then the standard histrionics takes over. But the mid-80s backprop people were very big on physics analogies, as I recall it, and that shaped the texture of the field.
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Replying to @Meaningness @michael_nielsen
True. Hopfield was a physicist.
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Replying to @IntuitMachine @michael_nielsen
And the Boltzman machine was a big deal for about a year then.
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Replying to @Meaningness @michael_nielsen
Yes, without a doubt these are physics inspired models. They kicked started the deep learning field. But, few use these models anymore.
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Replying to @IntuitMachine @michael_nielsen
Yes; I understand and applaud your frustration that potentially relevant physical methods and intuitions are now being ignored.
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Replying to @Meaningness @michael_nielsen
Honestly, I am not sure if it's relevant anymore. We've entered the realm of massive computation and likely biology is more important than physics.
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Replying to @IntuitMachine @michael_nielsen
As in, neuroscience is a better source of analogies?
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Replying to @Meaningness @michael_nielsen
Are they any closer in figuring out how to perform analogies?
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Uh… I wasn’t sure what you meant by “biology is more important than physics,” and this was a guess
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Replying to @Meaningness @michael_nielsen
I meant biology not neuroscience. The problem with neuroscience is that it's too reductionist. Brains are complex systems with emergent properties.
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