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So this exploits the fact that floating point numbers have finite precision (and perhaps uneven spacing) to generate non-linear operations?

That's actually a really cool usage of the specification!




Well, except that the author misunderstands the specification and how it is typically implemented on modern computers.


(I work at OpenAI.)

TensorFlow by default is built with denormals off (ftz=true), so denormals aren't relevant for the applications we're interested in. We have updated the post to indicate this — thanks for the feedback!




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