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. In September 2016, a research team at Google announced the development of the Google Neural Machine Translation system (GNMT) and by November 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. 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. System developed by Google to increase fluency and accuracy in Google Translate