In The Art of Doing Science and Engineering, Hamming gives this amazing sigmoidal formulation for the growth rate of computing power: e^(22(1-e^(-t/20))), with t=0 in 1943. That predicts 2.2 GHz for 2019, with is rather remarkably close to where we are.
Well, personally I've believed since the 80s that parallelism will win in the end. But I've been repeatedly too optimistic (i.e., flat wrong) about how rapidly that will happen.
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My guess is that eventually fairly parallelizable matrix-based ML methods mostly subsume what we currently think of as general-purpose computation. But right now you're not going to replace your single-threaded C or Javascript code with anything that looks like a neural net...
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It's a fun problem to think about - writing a web browser which is a neural net. (A friend of mine once taught his spam filter to play chess.)
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