With these packages, translators can manipulate the text in ways that seem very sophisticated compared to what you can do with track changes, the main tool that editors use. Professional translators, however, use software such as DejaVu, SDL Trados and MemoQ. Non-translators will be familiar with Google Translate and maybe with DeepL, which is producing very good output because it uses high quality translated texts as its source data, rather than the vast quantity of variable-quality data that Google uses. She talked about the future for language professionals, particularly with how fast machine learning is happening. Last year I attended the SENSE Conference, where the final keynote speaker was Sarah Bawa Mason, Chair of the Institute of Translation and Interpreting (ITI). This idea hasn’t gone without critique, but instead of worrying about the end of humanity, let’s narrow the scope somewhat: how is machine learning affecting the work of language professionals such as translators and editors? Translation software

At this point, machines will be able to self-improve at such a rate that it will signal the end of the human era as we know it.

We’re growing up fast, and, if you believe futurist Ray Kurzweil, the singularity is predicted to happen just 26 years from now.

It’s the last year where we, the world, are ‘teenagers’ in this century.

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