Easy take: calling linear algebra “quantum physics” and “artificial intelligence” is hype. Deeper: the huge influx of physicists into AI has produced an intellectual monoculture that isn’t capable of addressing key problems in the field.https://twitter.com/WIRED/status/1181437300414275584 …
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Maybe. Hopfield networks were popular then, so I guess lots of interest in physics crossover at the time. But SGD is a notion from mathematical optimization. The closer you look at the energy surface idea, the less it has anything to do with gradient descent.
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There are some papers from mit and but arguing about how deep learning is made possible by the renormalization group
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The same analogy is used in mathematical optimization. I suspect this is where ML vocabulary comes from. The natural source for ML ideas would be Statistical Mechanics. But you'll find few papers with this approach
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