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Researchers from The University of Texas at Austin and Northeastern University presented two papers at the 2017 Annual Meeting of the Association for Computational Linguistics that describe efforts to combine artificial intelligence with crowdsourced annotators and information encoded in domain-specific resources.

The work has the potential to improve general search engines, as well as niche ones like those for medical knowledge or non-English texts.

The research leverages the supercomputing resources at the Texas Advanced Computing Center to process large amounts of data and to train AI systems quickly.


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