From the outset, automatic translation was dominated by systems based on linguistic information, but then later other approaches opened up the way, such as translation memories and statistical machine translation which draw on parallel language corpora. Recently the neuronal machine translation (NMT) models have become the cutting edge in automatic translation and many translation agencies and well-known web pages are successfully using these technologies. One NMT model is a kind of statistical model comprising a group of simple deeply interconnected process units. The parameters of these models are estimated from parallel corpora using efficient automatic learning algorithms and powerful graphic processors. Applying these neural models to automatic translation requires words to be represented in the form of vectors and use recurrent neural networks in order to process phrases.