It’s already been six years now since Google revealed that Google Translate processes 146 billion words a day — three times more than what all the professional translators in the world combined can do in a month. That was 2016 and things haven’t really slowed down in the machine translation (MT) universe since.
Do you remember the last time when people were NOT talking about machine translation (MT)? We don't. Wherever you go, there’s someone talking about MT. With few exceptions, it seems like the only major disruptors in our industry over the past few decades have been breakthroughs in language technology.
19 August 2020
Some machine translation providers are holding out hope for MT systems that adapt to document context. Could this development eliminate the need for custom MT engines? Will context-enabled MT help MT achieve human parity? Will we still need to customize a few years from now? Let’s discuss further.
5 August 2020
One of the main reasons for implementing machine translation (MT) into localization workflows is that it saves money. And time. This time, let’s focus on money. In particular, cost savings.
19 February 2020
School is back in session! In this episode, Michael interviews a panel of localization professors—Max Troyer, Jon Ritzdorf and Jan Grodecki—about how they are preparing students for the future of localization. They discuss how curriculum should both ride the wave of current technology as well as teach students traditional critical skills. Other topics include the […]
25 September 2019