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[Exclusive] Zilliz Roundtable // Why Purpose-built Vector Databases Matter for Your Use Case

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Hybrid and Multi-Vector Search Features in Millvis two four

Exploring upcoming features in Millvis two four related to hybrid and multi-vector search, covering the concept of hybrid search with dense and sparse embeddings, best practices for generating embeddings, and the importance of purpose-built vector databases. The discussion dives into the need for fine-tuning embedding models, testing on customized datasets, and the challenges of determining ideal training data quantity and quality. Additionally, the chapter touches on neural priming, model evaluation with examples, and the significance of models like Colbert and late interaction models.

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