AI Writing: Threat or Opportunity for Language Service Providers?
Natural language generation (NLG) startups can help content creators write copy in multiple languages. But are AI writers a threat or an opportunity for LSPs?
Stay on top of how technology shapes the language, translation, and localization services industries
Natural language generation (NLG) startups can help content creators write copy in multiple languages. But are AI writers a threat or an opportunity for LSPs?
While intended primarily for informal interactions, new UK immigration guidelines suggest exceptional cases where staff might use a translation device instead of on-site or telephone interpreting.
In just three months, universities and tech companies released over two dozen papers on speech-to-speech translation (S2ST), highlighting continuing trends, new directions in research.
Open-sourcing large language models is catching on among tech giants, such as Google and Meta. Now comes BLOOM, whose 1,000 contributors designed it with multilingualism in mind.
UN interpreters blame technology for the decline in their working conditions. But the benefits of technology are real and should not be ignored by the interpreting community.
Among the platforms and workflows featured in Appen’s 2022 Investor Technology Day: Ontology Studio, which “productizes core components” of Appen’s “linguistic expertise.”
New research shows that automatic speech recognition and speech translation systems also improve when training data includes multiple instances of a given name.
Among the many things cooking at Meta: downloadable language packs for Android and iOS users to enjoy download-on-demand translation.
Meta AI wants to make large language models more accessible to researchers with the release of OPT-175B; advocates R&D transparency and a “research mindset.”
Google weighs in on how we should expect GPT-3-generated, multilingual content to figure in search rankings; explains why AI content violates its Webmaster Guidelines.
With translation automation, users are able to focus on high-value tasks rather than repeating workflows; new, less mechanical, more dynamic human roles here to stay.
What does Google’s 540-billion parameter language model, PaLM, mean for machine learning and the language industry? Experts weigh in.
From increasing productivity to allowing a more flexible, translator-centered, ergonomic workflow and workspace, this is how translators and post-editors benefit from speech technologies.
Ever wonder why your multilingual website isn’t ranking higher on Google Search despite all the SEO fairy dust — and dollars — you’ve thrown at it? Here are some reasons straight from a Google Expert.
ByteDance publishes research examining whether synthesized human speech could come close to the “impressive ability” of professional voice actors in dubbing.
As the language industry turns to speech-to-speech translation, Facebook AI partners with “AI community” Hugging Face to release speech-to-text translation models for four languages.
EU data anonymization tool released in pre-beta; final version will be an open-source, deployable toolkit in 24 EU languages.
The pandemic forced the European Parliament to quickly adopt remote interpreting and reconfigure on-site interpreting setups, with plans to establish regional interpreting hubs.
This is what happens when the CEOs of Smartling, XTM, and memoQ exchange views about trends in the TMS space and the future of the language market.
Processing uneditable file formats remains a headache for Translation Project Managers — but better tools, aspirational disruptors, and accelerated research may change that.
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