Given that neural networks run well with sloppy <= 8 bit precision, I wonder what kind of analog or optical computational arrangements could outperform digital hardware.
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The interesting point is questioning how much accuracy and precision is necessary; it seems to be less than most guesses, which may open up unconventional avenues.
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Even "good" VLSI transistors are lousy compared to discrete transistors. So there's already considerable art that goes into using them for neural networks in such a way as to make the overall error reasonable.
End of conversation
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