Vector database company Qdrant wants RAG to be more cost-effective [VentureBeat]

Qdrant’s BM42 is a new search model that extracts data from chunks of a document which it says makes vector search more efficient.

AI,Business,AI, ML and Deep Learning,algorithms,category-/Business & Industrial,hybrid,Qdrant,Retrieval-augmented generation (RAG),Search,search engines,Synthetic Data

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