Stay on top of how technology shapes the language services industries
Google publishes a tutorial on how to build a neural machine translation model from scratch in a push to accelerate adoption of its machine learning framework Tensorflow. Experts call the announcement important, but say production deployment requires much more than a tutorial. Continue reading
Europe continues to ramp up research in language technology. The number of papers published on machine translation in an academic journal has reached the highest number in more than a decade. Continue reading
CNBC reports that Amazon is looking to offer the translation technology it built for internal use to third parties. The move would be a direct challenge to Google Translate and the many other MT offerings by big tech companies. Continue reading
Google Translate’s top 10 words commonly translated into English include many words of admiration and several days of the week. Results for most languages are consistent with Japanese being the outlier. Continue reading
In 2013, the European Patent Office (EPO) partnered with Google to power its for-information-only Patent Translate portal. In May 2017, the EPO rolled out neural machine translation. And as Europe implements a new patent regime in the coming years, machine translation will play an ever more important role. Continue reading
Google Translate hides in plain site at annual developer conference. The talk was mostly about AI and the search giant’s proprietary processors that power neural machine translation. And then there was CEO Sundar Pichai introducing Google Lens, translation feature and all. Continue reading
Deloitte homes in on translation in report about how US government can leverage artificial intelligence to cut costs. Consulting firm proposes AI-augmented approach, which leaves the translator in control of the creative process and responsible for aesthetic judgments. Continue reading
Mark Zuckerberg looks forward to “making universal translation a reality” by open sourcing a new approach to neural machine translation. NMT expert impressed by faster training times of the new models but cautions against inflated quality expectations. Continue reading
Facebook Engineering Manager Necip Fazil Ayan discusses the social network’s key challenges with machine translating billions of posts and videos in dozens of languages; says his team’s work has barely begun. Continue reading
Under CEO Richard Harpham, who joined in May 2016, Cloudwords is opening up. The San Francisco-based marketing localization platform partners with translation productivity startup Lilt in a tech-to-tech tie-up. Continue reading
In addition to DIY, Google Translate, and crowdsourcing, YouTube also offers content creators to have their video captions translated by a select few language service providers through its translation marketplace. We checked in with one of those LSPs. Continue reading
More than half the tools used by technical translators in Germany are developed by SDL; while challengers, such as Kilgray and Across, also make a strong showing. More recent entrants into translation productivity market almost entirely absent. Continue reading
As language translation emerges as a yardstick for progress in artificial intelligence, high quality human translation data becomes a prized asset. The race for AI leadership sees Baidu host translation marathons across China to fill its data trove. Continue reading
While the folks at Skype Translator admit their technology still has a negative impact on conversation, many others a far less modest. A short history of hype, broken promises, and much ado about nothing. Continue reading
Yandex hires Microsoft veteran, folds machine translation unit into new machine learning division. Russian language industry researcher says while Yandex has a home court advantage, it will forever fight an uphill battle against Google. Continue reading
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