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Roughly three months ago, Facebook launched calls for research proposals in three subfields of natural language processing (NLP), the cross-disciplinary study of linguistics and AI concerned with computer-language interactions. It specifically sought “robust” deep learning approaches for NLP and computationally efficient NLP in addition to neural machine translation for low-resource dialects, ultimately in the pursuit of advancing cutting-edge research in machine translation.

That was just the start, it would seem. In a blog post today revealing 11 winning proposals among the 115 submitted from 35 countries, Facebook announced the AI Language Research Consortium, a community of partners it says will “work together to advance priority research areas” in NLP.

Details were tough to come by at press time, but Facebook says the newly formed group will foster collaboration to tackle challenging tasks like representation learning, content understanding, dialog systems, information extraction, sentiment analysis, summarization, data collection and cleaning, and speech translation. In addition to collaborating with Facebook researchers on multiyear projects and publications, members of the AI Language Research Consortium will receive funding for their research, participate in an annual research workshop, and receive access to auxiliary events at “major” NLP conferences.

“These research awards in NLP and machine translation were launched as a continuation of our long-term goal of supporting open research within the NLP community and strengthening collaboration between Facebook and academia,” wrote Facebook in a blog post. “Facebook believes strongly in open science, and we hope the consortium, as well as these research awards in NLP and machine translation, will help accelerate research in the NLP community.”


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Facebook’s AI Language Research Consortium might be perceived as an answer to Amazon’s Alexa Fund, which provides up to $200 million in venture capital funding to fuel voice technology innovation. All participants in the Alexa Fund are afforded access to tools such as software development kit previews, plus hands-on development support for hardware or software and placement at Amazon showcase events. Separately, the Alexa Fund Fellowship supports undergraduate- and graduate-level researchers working in fields like text-to-speech, conversational artificial intelligence, automatic speech recognition, and natural language understanding.

But the consortium’s mission appears to be more platform-agnostic than Amazon’s efforts — at least on its face. In that respect, it’s somewhat akin to “AI for good” programs like the grant portion of Google’s AI for Social Good, which provides funding to researchers applying at to solve some of the world’s toughest challenges, and Microsoft’s $125 million initiative targeting AI applications in ecology, accessibility, humanitarian action, and cultural heritage.

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