Translation automation has recently experienced a major shakeup – the emergence of neural MT*. This marks the start of a new journey of exploration into the opportunities and limitations of machine learning (ML) in translation and language technology more generally.
Two features stand out in this spectacular début. One is the rapid creation of a new ecosystem. The other is a pressing need to disrupt the current approach to sourcing language data for translation automation. The enriched ecosystem can help build a better language data pipeline for the entire industry, as both will depend on improved technology solutions.