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#96: How Words Get Their Meaning (feat. Gary Lupyan)

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Machine Learning - Distributional Semantics Vector Representations

The basic idea here is that there's this really cool approach to machine learning where you are able to basically construct these mathematical representations of quote unquote meaning. And the classical example circuit 2015 is you have a vector for king, a vector for queen, a vectors for man and women. If you subtract the queen vector from the king, and then you apply that vector to man, then what you get is a vector that most closely resembles out of all the words that you learn the word for female. Why? Because the same thing that separates king from queen is the same thing which separates male from female.

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