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Artificial—intelligence systems like Grammarly, an automated grammar—checker, are trained with data. for instance, translation software is fed sentences translated by humans, Grammarly's training data involve a large number of standard error—free sentences and human—corrected sentences. 1． The software then looks at a user's writing: if a line of words seems ungrammatical, it tries to spot how the generally supposed   mistake is most closely similar to   one from its training inputs.

2． Advances in language technology have been impressive in, for example, speech recognition, which involves another sort of statistical guess—whether or not a stretch of sound matches a certain line of words. 3． . It can rate the tone of an email before you send it, after being trained on texts that have been assessed by humans, for example as “admiring” or “confident”.

But grammar is the real magic of language, joining words into structures, joining those structures into sentences, and doing so in a way that maps onto meaning. 4． . Computers can analyse grammatical sentences fairly well, labeling things like nouns and verb phrases. But they struggle with sentences that are difficult to analyse, precisely because they are ungrammatical—in other words, written by the kind of person who needs Grammarly.

5． But computers don't work in meaning or intention, they work in formulae（惯用语）. Humans, by contrast, can usually understand even sentences that are not grammatically correct, because of the ability to guess the contents of other minds. Grammar—checking computers illustrate not how bad humans are with language, but just how good.