I started reading all pissed off because ML has been great for academia! Yes, this sounds like a fair point. It's probably the reason why Insel left Google after less than a year to start his own mental health startup.
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Replying to @BioProtean @o_guest
The fellow from Bell Labs responding in this thread makes some fair counter arguments. I feel like this would have been better framed as a critique of Google Research than ML, etc or corporate R&D but whatevs.
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Replying to @Arcanafex @BioProtean
I agree with this but it's still more complex than the thread even if taken in that light.
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Replying to @o_guest @BioProtean
This is a brilliantly evergreen response about every one of these sorts of universal statements/Twitter diatribes!
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To say ML/Al gives us no insight is factually wrong. Talk to a neuro and/or a cognitive scientist. E.g.http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003915 …
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Replying to @o_guest @BioProtean
Oh absolutely! My background is computational linguistics and ML has been pretty major tool in the academic field, to say the least.
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Replying to @Arcanafex @BioProtean
Yeah, as a tool it's useful too in my fields but I think it's — super super — valuable as a model as well.
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That paper, as an example, serves to show what deep networks, as models, are able to tell us about the mind. This is I think something really unexpected and extremely valuable for understanding the kind of processing the brain can do.
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Replying to @o_guest @BioProtean
This has been true in corpus linguistics and discourse modeling as well! And, really, too many areas of linguistics to bother summarizing!
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I mean sure in some sense but when I said "brain" meant literally.
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