Abstract: Retrieval-augmented generation pipelines store large volumes of embedding vectors in vector databases for semantic search. In Compute Express Link (CXL)-based tiered memory systems, ...

A study on vector database and AI integration identifies unstable indexing, weak cross-modal fusion, and rigid resource scheduling as key barriers. By introducing HNSW optimization, unified feature ...

IBM worked with Nvidia and Samsung to demonstrate a content-aware storage (CAS) system that can hold a 100-billion-vector database on a single server, work targeted at making retrieval-augmented ...

End-to-end semantic search system for arXiv papers using Qdrant vector database, OpenAI embeddings, FastAPI API, and CLI support — featuring batch ingestion, similarity search, and filtered queries.

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. Oracle announced a suite of agentic AI capabilities integrated directly into Oracle AI ...

Kioxia America, Inc. today announced the successful demonstration of high-dimensional vector search scaling to 4.8 billion vectors on a single server using its open-source KIOXIA AiSAQ™ approximate ...

Qdrant, the open-source vector search engine built in Rust for production workloads, announced it has secured $50 million in Series B funding will enable composable vector search as core ...

Qdrant, the open-source vector search engine built in Rust for production workloads, today announced $50 million in Series B funding led by AVP, with participation from Bosch Ventures, Unusual ...

Open-source vector search startup Qdrant Solutions GmbH today announced it has raised $50 million in early-stage funding to pave the way for smarter and more reactive artificial intelligence apps. AVP ...

BERLIN & NEW YORK--(BUSINESS WIRE)--Qdrant, the open-source vector search engine built in Rust for production workloads, today announced $50 million in Series B funding led by AVP, with participation ...