November South Bay Unstructured Data Meetup Talk
Dense Embeddings != Complete Search – a sneak peak of Milvus 2.5
Speaker: James Luan, VP of Engineering, Zilliz
Abstract:
Dense embeddings miss exact matches. Keyword search misses semantic meaning. Running two separate systems is a maintenance nightmare. We’ll show how Milvus 2.5’s hybrid search tackles this with a unified solution, preview its sparse-based BM25 implementation, and share performance numbers against current Elasticsearch-based architectures.
Key Points:
- Where dense embeddings fall short and how a unified system architectures address the search needs
– Sneak Peak of Milvus 2.5 – Quick look at our BM25 implementation and sparse vector optimizations
- Benchmark results comparing hybrid search latency and throughput vs ElasticSsearch
– What’s Next – Brief overview of upcoming features in our technical roadmap
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