Please provide an explanation of how large language models interpret prompts

I've got a pretty good handle on machine learning and how those LLMs are trained. People often say LLMs predict the next word based on what came before, using a transformer network. But I'm wondering, how can a model that predicts the next word also understand requests like 'fix the spelling in this essay,' 'debug my code,' or 'tell me the sentiment of this comment'? It seems like they're doing more than just guessing the next word.

I also know …

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