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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.
Step into the world of 'Global Ambitions' as we chat with Stephanie Harris-Yee of Argos Multilingual about their latest outsert, 'Global Ambitions,' and how...
Is the promise of AI detectors a false one? We dive into a Stanford University study revealing surprising biases in generative AI detectors. Join...
By Pascale Tremblay How can localization teams demonstrate the vital role of languages in a company’s success? Pascale Tremblay argues that language professionals can...
