Full technical report (23 exciting pages of bedtime reading):
Research blog post: https://research.googleblog.com/2016/09/a-neural-network-for-machine.html
I'm very excited to announce that our new neural machine translation system closes the quality gap between the existing Google Translate production system and human quality translations by 58% to 87% for a variety of different language pairs (see table below, from the technical report we published today). This work has been a close collaboration between the Google Brain team (g.co/brain) and the Google Translate team.
Thanks to lots of hard engineering work and the computational efficiency of our Tensor Processing Units (see report), we are also rolling these benefits out to users of Google Translate, starting today with Mandarin to English as the first language pair live in production that uses this new system. We'll be rolling out many more language pairs over the coming weeks.
This highlights the success of neural models at more accurately capturing the complexities of real human language, and is a powerful demonstration of the research our group has been doing on language understanding.
(Edit: moved arxiv and blog link above the fold)