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With the democratization of AI, an engineer can build an MT model in one day. However, beating Google or DeepL in quality, performance, and market presence is another story. So, who are the teams that are able to compete, stand tall, and beat the odds in the market of MT? Here are some of our top picks.
Data journalists at The Economist used information from Spotify to identify several trends in how local communities across the world listen to music —...
A team of researchers at the University of Toronto has introduced a new framework for interpreting slang in natural language processing (NLP).
A recently introduced senate bill in Oregon is drumming up a bit of controversy among healthcare interpreters and language service providers (LSPs) that work...
