How to train your large language model
A new technique is speeding up the process
It is no secret that building a large language model (LLM) requires vast amounts of data. In conventional training, an LLM is fed mountains of text, and encouraged to guess each word before it appears. With each prediction, the LLM makes small adjustments to improve its chances of guessing right. The end result is something that has a certain statistical “understanding” of what is proper language and what isn’t.
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This article appeared in the Science & technology section of the print edition under the headline “AI boot camp”
From the March 16th 2024 edition
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