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Article summary:

1. Organizing notes is difficult because it's hard to know what you'll use them for in the future.

2. AI models like GPT-3 can help solve this problem by automatically tagging and linking notes, enriching notes as they're written, and resurfacing key information from previous notes.

3. LLMs can also synthesize notes into research reports, eliminating the need for manual tagging and linking.

Article analysis:

The article provides a comprehensive overview of how AI models like GPT-3 can be used to improve note organization. The author makes several claims about the potential benefits of using these models, such as automatically tagging and linking notes, enriching notes as they're written, and resurfacing key information from previous notes. However, there is no evidence provided to support these claims or any discussion of potential risks associated with using AI models for note organization. Additionally, the article does not explore any counterarguments or present both sides of the argument equally. Furthermore, the article appears to be promotional in nature as it suggests that readers consider sponsoring its smart long-form essays on tech, AI, and productivity. As such, while the article provides an interesting overview of how AI models could potentially be used to improve note organization, it should be read with caution due to its lack of evidence and potential bias towards promoting its own services.