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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That's interesting... so the monoculture may be specific to deep learning as such; something that developed just within that narrow field. (
@michael_nielsen, maybe this is the point you were making too?)
Pretty much. There are useful ideas from physics in deep learning research, but I don't think any (currently) really key/dominant ideas are from physics. Maybe I'm not thinking of one?
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I mean... the whole thing looks like physics to me? You’re shaking a ball on an energy surface.
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Hmm, I’m wondering if the disconnect here is that I learned backprop in ~1986, and maybe much more use of physical analogies was prevalent then?
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Naftali Tishby attempted a couple years ago to introduced his flavor of physics to the study. His paper got rejected. The following year another paper that criticized Tishby's formulation came out. This paper was accepted. It's NIH syndrome.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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There isnt yet but growing interest in bringing more non-equilibrium thermodynamics, fluctuation theorems into ML/DL. The area of manifold learning in particular looks like a great area of intersection.
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The language of physics is too foreign for deep learning researchers. Think for a moment here, these people have either statistics or comp.sci. backgrounds. What kind of math do they cover!
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