Neural machine translation systems offer an opportunity for real progress in the quality of translations produced by machines. However, machine translation still produces unacceptably poor quality content, especially for established brands that (rightly) set a very high bar for their content and brand tone of voice (that can only be set by a good terminology work).
Given the huge effort underway to vastly improve machine translation, it’ll likely redefine the role of humans in the translation process.
Shouldn't we be looking into ways of making termbases work together with machine translation engines and all the other available CAT-environment tools to contribute quality content? Terminologists need to rise to the challenge of integration with other CAT-environment tools, so that their assets can find their way into the general workflow. This can be achieved only through close cooperation with the developers of technical solutions and by understanding the specific needs of all categories of end user.
Translation memory is already able to facilitate faster human translation, providing translators with words and phrases that have already been translated, but only terminology can tell you how something should be translated in the future.