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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.
In this conversation, Will Rowlands-Rees, Chief AI Officer at Lionbridge, discusses the transformative impact of AI on the localization industry and the critical role...
Multimedia post-production offers various ways to reach your audience. The most popular of these include dubbing, voiceovers, and subtitling. Each method has its own...
With the democratization of AI, an engineer can build an MT model in one day. However, beating Google or DeepL in quality, performance, and...
