Simon Willison discusses a novel approach to content tagging proposed by Doug Turnbull, which involves having a large language model hallucinate potential tags rather than classifying against an existing vocabulary. This method is particularly useful for large, older content archives where manual tagging is impractical. The LLM generates new, descriptive tags, and then vector embeddings are used to match these generated tags to the closest existing ones in the corpus. AI
IMPACT This method could improve content organization and searchability for large archives by leveraging LLMs to generate descriptive, novel tags.
RANK_REASON Blog post discussing a novel method for content tagging using LLM hallucination.
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