Google Translate is a tool that most of us already know and use. As one of the more popular Google products, it currently serves 500 million monthly users. While Google Translate historically may have been helpful for casual browsers of the internet, it’s not really useful enough to rely on completely for every day conversation, nor for a comprehensive understanding of foreign website.
Google’s recent update of Google Translate, however, has changed that. As of December last year, Google introduced AI into Google Translate, making the product astoundingly better. NYTimes shares the below example:
“Uno no es lo que es por lo que escribe, sino por lo que ha leído.”
With the original Google Translate: “One is not what is for what he writes, but for what he has read.”
With the new A.I.-rendered version: “You are not what you write, but what you have read.”
The difference is stark. Not only has the improvement enabled more coherent and seamless translations, the Google Neural Machine Translation tool now is able to link between two different languages that haven’t been previously linked. That is, Google Translate (idiomatically speaking) has it’s own language that it translates all languages to, thus enabling it to translate two different languages that it hasn’t been explicitly linked to. This improvement opens the door to more language pairings without much of the previous heavy lifting of explicitly linking one language and translating it to another.
This change has interesting implications on the future of news. It makes international news articles accessible to everyone. It allows journalists much easier and faster (and more reliable) access to sources–whether it be other people or documentation and data. More data will simply be more accessible.
It also may have implications on the labor force in the news industry–local speakers may not eventually be needed for reporting. How might this change the type of coverage we get? In a time when some news articles are already written by bots, will Google Translate improve our coverage because we can “understand” more? Or will this make news stories even more impersonal and spotty as we miss cultural nuances and context that only a local expert can provide? The potential implications seem both exciting, and daunting.
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