Facebook, Amazon, Twitter Research ‘Blind Spot’ in Modern Machine Translation
New paper by Facebook, Amazon, Twitter, and University of Melbourne examines vulnerability of systems using back translation to attacks on monolingual training data.
New paper by Facebook, Amazon, Twitter, and University of Melbourne examines vulnerability of systems using back translation to attacks on monolingual training data.
In the November 2020 edition of our buyer tracker, we provide SlatorPro subscribers with a selection of some of the most important changes among buy-side decision-makers.
Our glimpse into the Twittersphere gives an overview on the types of tweets about the language industry that are popular during lockdown.
Preferred social networks for industry insights? Increase in translator scams? Industry reliance on freelancing versus in-house employment? Support for Dutch linguists on strike?
Days before California’s gig worker bill takes effect, journalists and photographers sue state. American Translators Association doubles down in fight to exempt translators and interpreters.
Google has admitted machine translated content is a challenge to ranking algorithms. Researchers at the University of Tokyo may have found a solution: back-translation.
Appen pays up to USD 300m for automated data annotation platform Figure Eight, preempting an emerging threat to its crowd-based business model.
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