Using AI to match human performance in translating news from Chinese to English
Compare this to one of Google's blog post promoting their MT research: <a href="https://research.googleblog.com/2016/09/a-neural-network-for-machine.html" rel="nofollow">https://research.googleblog.com/2016/09/a-neural-network-for...</a><p>It is:<p>1) More accurate, compared to hyperbole like e.g. "Bridging the Gap between Human and Machine Translation" we have right there in the title the domain: news.<p>2) A more impressive result. This result is on an independently set up evaluation framework, compared to Google's which used their own framework.<p>Compare further the papers:
<a href="https://arxiv.org/pdf/1609.08144.pdf" rel="nofollow">https://arxiv.org/pdf/1609.08144.pdf</a>
<a href="https://www.microsoft.com/en-us/research/uploads/prod/2018/03/final-achieving-human.pdf" rel="nofollow">https://www.microsoft.com/en-us/research/uploads/prod/2018/0...</a><p>These researcher appear to have been much clearer about what they're actually claiming, and also used more standard evaluation tools (Appraise) and methodology rather than something haphazardly hacked together.