Three ideas from linguistics that everyone in AI should know


Everybody knows that large language models like GPT-3 and LaMDA have made tremendous strides, at least in some respects, and powered past many benchmarks, and Cosmo recently described DALL-E but most in the field also agree that something is still missing. A growing body of evidence shows that state-of-the-art models learn to exploit spurious statistical patterns in datasets... instead of learning meaning in the flexible and generalizable way that humans do." Since then, the results on benchmarks have gotten better, but there's still something missing. Reference: Words and sentence don't exist in isolation. Language is about a connection between words (or sentence) and the world; the sequences of words that large language models utter lack connection to the external world.

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