It’s a common refrain, that’s true, but machine translation engines really have come a long way. The days when MT was a novelty with amusing errors is long gone; the quality of machine translations has gone up enough to be useful in industrial and commercial contexts today.
The key difference between then and now boils down to one thing: neural machine translation (NMT). Neural machine translation is a form of MT that uses neural networks, which can process massive amounts of translation data with relative efficiency, increasing the quality of translations exponentially. Today, all MT engines use neural machine translation.
An MT engine that is well-trained in translating for a specific sector is capable of producing information that can generally be understood. In the context of the case at hand—localizing support pages—this is precisely the point.
The language on a support page doesn’t need to have dominican republic mobile database the polish and style of, say, ad copy, after all. for users to know what to do without having to open a ticket for human assistance. MT today is more than capable of doing this, compared to the past decade, or even the past five years.
Zendesk is able to create support pages in a different language that are of adequate quality for use, largely through machine translation. That in itself is a remarkable feat, and makes a good case for allaying the fear of stakeholders who are still skeptical or on the fence when it comes to using machine translation in their own business.