Neural Machine Translation (NMT), one of the most important topics in deep learning, has gained much attention from the industries and academia over the last few years. In order to create simple models out of the complex ones, tech giant Google has been doing a lot of innovations in the domain of human to machine and machine to human translations for quite a few years now. Back in 2017, the tech giant introduced a solution to use a simple Neural Machine Translation (NMT) model to translate between multiple languages where the researchers merged 12 language pairs into a single model. Models into three types which are many-to-one, one-to-many and many-to-many models. Recently, the researchers at Google AI Team built a more enhanced system for neural machine translation (NMT) and published a paper known as "Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges".

Paris, France based language solution provider Systran has launched its Neural Machine Translation engine. Its PNMT (Pure Neutral Machine Translation) gives organisations access to translation, close to human fluency and adapted for customers across industries. Translation services mean that companies can deploy their business strategy in multiple countries at the same time to improve their time to market in different countries. The Systran solution can communicate in over 140 language combinations. It has made a client beta program and an online demo available for customers to try the engine.