The new translation engine was first enabled for eight languages: to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish in November 2016. GNMT did not create its own universal interlingua but rather aimed at finding the commonality between many languages using insights from psychology and linguistics. GNMT's proposed architecture of system learning was first tested on over a hundred languages supported by Google Translate. The result is then rearranged and adapted to approach grammatically based human language. By using millions of examples, GNMT improves the quality of translation, using broader context to deduce the most relevant translation. Google Translate's NMT system uses a large artificial neural network capable of deep learning. Since then, Google Translate began using neural machine translation (NMT) in preference to its previous statistical methods (SMT) which had been used since October 2007, with its proprietary, in-house SMT technology.

In November 2016, Google Neural Machine Translation system (GNMT) was introduced. Ng's work has led to some of the biggest breakthroughs at Google and Stanford. The Google Brain project was established in 2011 in the 'secretive Google X research lab' by Google Fellow Jeff Dean, Google Researcher Greg Corrado, and Stanford University Computer Science professor Andrew Ng. The GNMT network can undertake interlingual machine translation by encoding the semantics of the sentence, rather than by memorizing phrase-to-phrase translations. GNMT attempts to translate whole sentences at a time, rather than just piece by piece. With the large end-to-end framework, the system learns over time to create better, more natural translations. GNMT improves on the quality of translation by applying an example-based (EBMT) machine translation method in which the system 'learns from millions of examples'. Google Neural Machine Translation (GNMT) is a neural machine translation (NMT) system developed by Google and introduced in November 2016, that uses an artificial neural network to increase fluency and accuracy in Google Translate. System developed by Google to increase fluency and accuracy in Google Translate

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