Bringing Neural Machine Translation to Production at Large Scale

ABSTRACT:

Deep neural networks for machine translation have produced impressive research results in the last few years (notably from the University of Edinburgh), greatly improving over formerly state-of-the-art statistical methods. Bringing these systems into production for end users presents unique challenges: of scale, speed, features, translation quality, and the ability to diagnose and fix unexpected behavior from deep neural networks. This talk will cover some of those challenges that Google has overcome in converting a large fraction of Google Translate traffic to neural translation, and some of the challenges that still remain.

BIO:

Macduff Hughes is an Engineering Director at Google, and has led the Translate team there since 2012.