![]() And so by doing this sort of mining through and pattern recognition, the machines figure out how to translate not just phrase by phrase but entire thoughts, sentences, paragraphs. ![]() And the algorithms then mine through the data to look for patterns. You take that data, and you load it into the computers. And the way it works is, you take a boatload of data - translations - really good translations, for example, between Chinese and English. So what these companies such as Google are doing now is they're moving to a pattern recognition. You could have a linguist, a human expert, sit down and dictate all the rules going from one language to another, but that would be a really tedious, exhausting process that arguably, as it seems, doesn't really turn out the kinds of results you want because a lot of languages aren't structured in parallel form. SHAHANI: Well, you know, so it's Google as well as Facebook, Microsoft, Baidu and a bunch of other tech companies, leading tech companies who are moving to an AI system here. MCEVERS: So how is Google using artificial intelligence to improve translation? NPR's Aarti Shahani is with us to talk about this. Now Google says it can do it better thanks to artificial intelligence. It reads, (reading) life gave me the opportunity to vote in my country on this day - so exciting. Web-based translators have made it much easier to understand things that are written in other languages, but they are not perfect, like this example.įacebook recently translated a Colombian voter's post from the original Spanish to English. And now for something back on the ground.
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