The work -- described in a Microsoft blog post on March 14 -- involves using deep neural networks, a method of training AI systems, to help them deliver more realistic and accurate translations. It also employs a number of different AI-training methods, including dual learning, deliberation networks and joint training to try to mimic how humans learn.
The group says they've achieved human parity on a test set of news stories called newstest2017, which was developed by industry and academic partners and made available at a research conference last fall. The test set included about 2,000 sentences from a sample of online newspapers that had been professionally translated.
Microsoft's latest AI milestone was achieved by three research teams in Microsoft's Beijing and Redmond research labs working together. This is a research effort at this point and Microsoft hasn't released results of testing the system on real-time news stories.
There's no word on when, how or if Microsoft plans to bring this work to its Microsoft Translator service, as this is still a research project, at this point.
Update: Here's a bit more color from Microsoft on availability.
"We're working to bring this to production as soon as possible, but we have nothing to announce at this time," said a company spokesperson in response to my question as to when this technology could become commercially available.
"In the future, these systems could be applied to Microsoft's commercially available translation tools such as Microsoft Translator, which is available as an app, API, and also the translation engine for many Microsoft products including Office, Bing and others," the company spokesperson said.