A jump in the fluency of Google’s language software will help efforts to make chatbots less lame.
Google’s latest advance in machine learning could make the world a little smaller.
The company is reëngineering its translation service after Google researchers invented a system that is significantly more accurate. In a competition that pitted the new software against human translators, it came close to matching the fluency of humans for some languages, such as when translating from English to Spanish or Portuguese.
Google has already begun rolling out the new system for translations from Chinese to English (see examples showing the improvement). The company expects to replace its current translation system altogether.
Making it easier to read Web pages or exchange messages across language barriers could help people around the globe communicate with one another. Google researcher Quoc Le says Google’s big translation upgrade could also lead to improved relations between people and machines.
Ideas at work in the new translation system could help software learn to do harder things such as read Wikipedia and then answer complex questions about the world, says Le, who was one of MIT Technology Review’s35 Innovators Under 35 in 2014.
Google’s new translation system was built using a technique known as deep learning, which uses networks of math functions loosely inspired by studies of mammalian brains (see “10 Breakthrough Technologies 2013: Deep Learning”). It triggered the recent flood of investment in artificial intelligence by producing striking progress in areas such as image and speech recognition.
Since 2014, researchers at Google have been investigating how deep learning might also deliver a shot in the arm to translation. Le says the latest results show that time has now come.
A paper released by Google includes results from translating from English into Spanish, French, Portuguese, and Chinese, and from each of those languages into English. When people fluent in two languages were asked to compare the work of Google’s new system against that of human translators, they sometimes couldn’t see much difference between them.
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