Machines learn language better by using a deep understanding of words
Originally shared by Ward Plunet
Machines learn language better by using a deep understanding of words
Computer systems are getting quite good at understanding what people say, but they also have some major weak spots. Among them is the fact that they have trouble with words that have multiple or complex meanings. A new system called ELMo adds this critical context to words, producing better understanding across the board. To illustrate the problem, think of the word “queen.” When you and I are talking and I say that word, you know from context whether I’m talking about Queen Elizabeth, or the chess piece, or the matriarch of a hive, or RuPaul’s Drag Race. This ability of words to have multiple meanings is called polysemy. And really, it’s the rule rather than the exception. Which meaning it is can usually be reliably determined by the phrasing — “God save the queen!” versus “I saved my queen!” — and of course all this informs the topic, the structure of the sentence, whether you’re expected to respond, and so on.
https://techcrunch.com/2018/06/15/machines-learn-language-better-by-using-a-deep-understanding-of-words/
Machines learn language better by using a deep understanding of words
Computer systems are getting quite good at understanding what people say, but they also have some major weak spots. Among them is the fact that they have trouble with words that have multiple or complex meanings. A new system called ELMo adds this critical context to words, producing better understanding across the board. To illustrate the problem, think of the word “queen.” When you and I are talking and I say that word, you know from context whether I’m talking about Queen Elizabeth, or the chess piece, or the matriarch of a hive, or RuPaul’s Drag Race. This ability of words to have multiple meanings is called polysemy. And really, it’s the rule rather than the exception. Which meaning it is can usually be reliably determined by the phrasing — “God save the queen!” versus “I saved my queen!” — and of course all this informs the topic, the structure of the sentence, whether you’re expected to respond, and so on.
https://techcrunch.com/2018/06/15/machines-learn-language-better-by-using-a-deep-understanding-of-words/
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