In early September, Copenhagen will become the center of the machine translation universe as hundreds of researchers gather in the Danish capital to learn whose system performs best. Continue reading
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In the global enterprise, content submitted for machine translation is often highly sensitive. SDL’s engineers and linguists have teamed up to develop neural machine translation that produces high-quality output and can be deployed on-premise or in a Private Cloud with minimal support. Continue reading
Facebook says it has completed transitioning to neural machine translation models in its backend systems. Factoring in slang, typos, abbreviations, and all shades and nuances of social media posts, will this really result in more fluent translations? Continue reading
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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
FIFA’s Deputy Head of Language Services talks about what it takes to communicate to the world’s three billion football fans, why they prefer to work with freelance translators for most of their material, and why cost is only one factor in their outsourcing decision. 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
In 2015, four leading European institutions and companies set out to solve machine translation’s four main problems: training, context, scalability, and data collection. After a brief scare when Google Translate went neural, the project is now in beta and set for enterprise-grade release in Q4 2017. 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
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
Results of a survey among hundreds of machine learning researchers say machines will overtake (amateur) human translators by 2024. Translating film subtitles will take another two years, while cracking an entirely new language Rosetta Stone-style another eight years. Continue reading
E-commerce platform GetYourGuide localizes 30,000 tours and activities into 14 languages in real-time. An early adopter of adaptive machine translation, the company works closely with professional translators for much of its content, but prefers machine translation for customer reviews. 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
Six new automated translation projects will receive funding from the EU’s Connecting Europe Facility (CEF) program in the telecommunications sector to improve multilingual support for public sector organizations. Continue reading
Nine-year-old language service provider started by thebigword veteran reports 28% revenue growth and 315% jump in pre-tax earnings. Director Robert Timms on how MT is not cannibalizing volumes and why he is frustrated with UK government procurement. Continue reading
We asked our readers and they said cold calling is still the most effective way to generate leads, think machine translation hasn’t really moved the needle yet, and 20% believe human translators will run at 1,300 words or more per hour by 2022. Continue reading
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