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by traverseda
852 days ago
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It's not the application of LLMs for your notes, it's the application of your notes for an LLM. Like if you're running a custom code-generation LLM, it could refer back to parts of your notes using retrieval aided generation to get some more context on the work you're having it do. But yes, a good application is probably a ways away. Still, LLM vector embedding make a good search engine pretty easy to implement, especially if you're working with small sets of well curated data where exact keyword matching might not work great. Like if you search for "happy" you could get your happiest journal entries, even if none of them explicitly mention the word happy. |
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