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This article discusses how Google Translate functions. Google Translate is a relatively accurate and easy-to-use translator. At first, the system required millions of human-generated translations of texts to identify patterns, in order to provide a pretty accurate translation. Also during this early period, the translator would use English as an intermediary language-languages were translated to English and then from English to the target language. The translator was decent at translating short excerpts, but as the texts got longer, there is a decline in the quality of the translations. In 2016, Google announced they were shifting to a neural network machine learning process, which is supposed to attempt look at the full context of the texts to eliminate discrepancies in translations. This way instead of an intermediary language, the system can just translate from one language to another.

A traveling journalist in Beijing utilizes both Baidu (China's version of Google) and Google voice-translation apps with mixed results. You speak into the apps, they listen and then translate into the language you choose. They do it in writing, by displaying text on the screen as you talk; and out loud, by using your phone's speaker to narrate what you've said once you're done talking. Typically exchanges are brief: 3-4 turns on average for Google, 7-8 for Baidu's translate app. Both Google and Baidu use machine learning to power their translation technology. While a human linguist could dictate all the rules for going from one language to another, that would be tedious, and yield poor results because a lot of languages aren't structured in parallel form. So instead, both companies have moved to pattern recognition through "neural machine translation." They take a mountain of data - really good translations - and load it into their computers. Algorithms then mine through the data to look for patterns. The end product is translation that's not just phrase-by-phrase, but entire thoughts and sentences at a time. Not surprisingly, sometimes translations are successes, and other times, epic fails. Why? As Macduff Hughes, a Google executive, notes, "there's a lot more to translation than mapping one word to another. The cultural understanding is something that's hard to fully capture just in translation."

This article talks about how the Google Translate tool recently started using a neural network to translate between some of its most popular languages. The system is now so clever it can do this for language pairs on which it has not been explicitly trained.