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Automatic Differentiation and Ubiquitous Adaptive Computing

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Automatic Differentiation and Ubiquitous Adaptive Computing

Barak A. Pearlmutter

Maynooth University, Ireland barak.pearlmutter@mu.ie

Abstract. Computer science has worked for decades to realize a sort of pantheistic dream, in which the inanimate objects that surround us are endowed with a vital computational essence and become our magi- cal servants. The hardware is coming along nicely, but the vital essence is static: despite their remarkable abilities, our servants are bullheaded and unchanging. In order to make such complex systems adaptive, in a variety of senses, we need for adaptation to be compositional and auto- matic. As a step in that direction, we’ve tried to push a simple adaptive mechanism—gradient optimization—into fully general settings, complete with iteration and nesting and Turing equivalence. People now call this

‘differentiable programming’. I’ll describe some of the automatic differ- entiation underpinnings that seem poised to help make the computers that surround us a bit less annoying.

Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

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