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This same technology that enabled neural machine translation to improve machine translation is now finding its way into seemingly unrelated products (think ChatGPT or Dall·E). The translation “problem” has not been solved with the latest advancements in NMT, but there are lessons to be learned in other professions from how the professional translation community has been affected by and adapted to the widespread use of NMT both by translators and by end users.
Venture into the intricate nexus of AI and its ever-evolving role in the media and entertainment world. With generative AI making waves in content...
Amir Kamran and Amir Soleimani from Taus unpack Quality Estimation (QE) as the missing link between machine translation at scale and human-quality outcomes. They...
By Jonathan Otis After a significant slowdown in 2023, the language sector’s M&A landscape rebounded this year, with nearly every language service provider that...
