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The latest vector embeddings news, distilled by AI into sharp ~100-word summaries. ByteBrief tracks vector embeddings across dozens of tech sources and brings you only what matters, updated hourly. Tap any story for the full brief, or open the original source.
Simon Willison's blog has 1,856 tags, too many for one LLM call. Doug Turnbull's solution: have the model invent tags, then use vector embeddings to match them to the closest existing tags. The example prompt shows tag shape examples.
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