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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.
Supertext is making a bold move by putting AI translation at the center of its strategy—but with a twist. CEO Sam Laübli explains how...
There’s no better organization to guide women — and the industry — toward a brighter future than Women in Localization. The leading community and...
This panel brings together language policy advocates, legal experts, and industry leaders to unpack the implications of recent executive orders under the Trump administration—particularly...
