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 ...

Automatic text-to-vector conversion using Dify's embedding models Dense and hybrid (dense + sparse BM25) similarity search Flexible point storage with standard Qdrant format support Full collection ...

Enterprise data teams moving agentic AI into production are hitting a consistent failure point at the data tier. Agents built across a vector store, a relational database, a graph store and a ...

Oracle announced a suite of agentic AI capabilities integrated directly into Oracle AI Database, enabling AI agents to securely access enterprise data where it already exists, rather than requiring ...

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To continue reading this content, please enable JavaScript in your browser settings and refresh this page. Preview this article 1 min Vector Systems is betting big on ...

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 ...

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, ...

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 ...