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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 captivating interview from LocWorld, join Spence Green, the founder of Lilt, as he delves into the company’s trailblazing journey in the world...
In the last installment of The Lab for the year, columnist Mark Shriner takes a look at the past year and predicts some trends...
By Ewandro Magalhães The author reflects on the slow pace of technological progress in the interpretation space, from the advent of simultaneous interpreting in...
