Google is updating its translation service by implementing machine learning also in the offline application, here’s how to use it in Italian
Google Traduttore is a faithful ally for those who need help translating a word, a sentence or a small text from a foreign language. In recent times, the implementation of machine learning algorithms has exponentially improved the quality of translation, making Google Translate even more reliable.
In particular, it is the Google Traduttore app that has benefited most from machine learning: the implementation of Neural Machine Learning, coupled with increasingly powerful mobile devices, has allowed the Mountain View-based company to make Google Traduttore work offline.In this way, it is no longer necessary to have an active data connection (or be connected to a Wi-Fi network) in order to take advantage of the power of Big G’s translation algorithms, but simply launch the app and type the phrase to be translated. A very handy feature especially when you’re abroad and need to translate a street sign or get directions.
How Google Translate works offline
With the June 2018 update, Gloogle Traduttore offline is also available in Italian (and 58 other languages). In order to use it, all you have to do is update the application, open the menu and, among the various items present, press on Offline Translations. This will take you to the list of languages supported by Google Offline Translator with Neural Machine Learning. At this point you’ll just have to download the data package of the language (or languages) you are interested in and that’s it. Even without a data connection you’ll be able to take advantage of the machine learning capabilities for flawless translations, or almost flawless.
But why is the new version of Google Translate, with artificial intelligence, better than the old one? It’s easy to say: machine learning algorithms allow Big Gi’s service to refine its capabilities based on both data from other translations and user suggestions. It will thus be able to pick up more nuances of the spoken language and return translations more similar to natural language.