Sinofsky: State-of-the-art machine translation still relies on 1970s NLP
Steven Sinofsky · a16z Podcast | Revenge of the Algorithms (Over Data)... Go! No? · Jan 2, 2019 · at 17:54
Steven Sinofsky explains how modern machine learning systems rely on legacy rule-based software for preprocessing and bookkeeping.
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“The best example for me of that is how everybody said machine learning was going to replace all of natural language processing. But if you dig into any of the work that's been going on, even the most state of the art translation, which, you know, goes any language pair to any language pair. Well, The input and the output all rely on the old school, like from the 19 seventies, natural language stuff, just to do some very basic bookkeeping.”
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