One of the most promising applications of hyperdimensional language processing is a class of AI systems called transformers. These are deep-learning models that use a mechanism called “attention” to focus their computational power on the most relevant parts of their input data—in much the same way that the human neocortex lets us direct our own attention toward the information most vital to our thinking. Transformers are trained on massive amounts of text, which they encode as “tokens”—usually a combination of parts of words, words, and strings of words. The model then uses a very large number
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