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Meta's AI machine translation research to help break language barriers


Meta has announced that it has built and open-sourced'No Language Left Behind' NLLB-200, a single Artificial Intelligence (AI) model that is the first to translate across 200 different languages, including 55 African languages with state-of-the-art results. Meta is using the modelling techniques and learnings from the project to improve and extend translations on Facebook, Instagram, and Wikipedia. In an effort to develop high-quality machine translation capabilities for most of the world's low-resource languages, this single AI model was designed with a focus on African languages. They are challenging from a machine translation perspective. AI models require lots and lots of data to help them learn, and there's not a lot of human-translated training data for these languages.

Meta's new AI could tear down the language barrier once and for all


Meta has published a massive new artificial intelligence (AI) model capable of translating between more than 200 different languages. Trained using one of the world's most powerful AI supercomputers, the No Language Left Behind (NLLB) model is already supporting advanced translation features across Meta's suite of apps and services. "The advances here will enable more than 25 billion translations every day across our apps," said Mark Zuckerberg, Meta CEO. "The AI modeling techniques we used are helping make high-quality translations for languages spoken by billions of people around the world. "Communicating across languages is one superpower that AI provides, but as we keep advancing our AI work it's improving everything we do - from showing the most interesting content on Facebook and Instagram, to recommending more relevant ads, to keeping our service safe for everyone".

How Google is using emerging AI techniques to improve language translation quality


Google says it's made progress toward improving translation quality for languages that don't have a copious amount of written text. In a forthcoming blog post, the company details new innovations that have enhanced the user experience in the 108 languages (particularly in data-poor languages Yoruba and Malayalam) supported by Google Translate, its service that translates an average of 150 billion words daily. In the 13 years since the public debut of Google Translate, techniques like neural machine translation, rewriting-based paradigms, and on-device processing have led to quantifiable leaps in the platform's translation accuracy. But until recently, even the state-of-the-art algorithms underpinning Translate lagged behind human performance. Efforts beyond Google illustrate the magnitude of the problem -- the Masakhane project, which aims to render thousands of languages on the African continent automatically translatable, has yet to move beyond the data-gathering and transcription phase.

Teaching AI to translate 100s of spoken and written languages in real time


For people who understand languages like English, Mandarin, or Spanish, it may seem like today's apps and web tools already provide the translation technology we need. But billions of people are being left out -- unable to easily access most of the information on the internet or connect with most of the online world in their native language. Today's machine translation (MT) systems are improving rapidly, but they still rely heavily on learning from large amounts of textual data, so they do not generally work well for low-resource languages, i.e., languages that lack training data, and for languages that don't have a standardized writing system. Eliminating language barriers would be profound, making it possible for billions of people to access information online in their native or preferred languages. Advances in MT won't just help those people who don't speak one of the languages that dominates the internet today; they'll also fundamentally change the way people in the world connect and share ideas.

Behind No language Left Behind


What if you didn't need English to translate? Meta's new and improved open source AI model'NLLB-200' is capable of translating 200 languages without English! "Communicating across languages is one superpower that AI provides, but as we keep advancing our AI work it's improving everything we do--from showing the most interesting content on Facebook and Instagram, to recommending more relevant ads, to keeping our services safe for everyone", says Mark Zuckerberg, CEO, Meta. Accessibility through language ensures that the benefits of the advancement of technology reach everyone, no matter what language they may speak. Tech companies are assuming a proactive role in attempting to bridge this gap.