Large language models are built by using supervised learning to train a model to repeatedly predict the next word. For example, if an AI system has read on the Internet a sentence like my favorite drink is lychee bubble tea, then the single sentence would be turned into a lot of A to B data points for the model to learn to predict the next word.
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Unknown titleate new texts by repeatedly predicting what is the next word they should output. Given the widespread attention on LLMs, let's look briefly on the next slide in greater detail at how they work. <span>Large language models are built by using supervised learning to train a model to repeatedly predict the next word. For example, if an AI system has read on the Internet a sentence like my favorite drink is lychee bubble tea, then the single sentence would be turned into a lot of A to B data points for the model to learn to predict the next word. Specifically, given this sentence, we now have one data point that says, given the phrase my favorite drink, what do you predict is the next word? In this case, the right answer is give Summary
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