Oracle tackles database infrastructure with its Globally Distributed AI Database, aiming to ensure zero data loss for mission ...
Two years ago, Microsoft launched its first wave of “Copilot+” Windows PCs with a handful of exclusive features that could ...
A study on vector database and AI integration identifies unstable indexing, weak cross-modal fusion, and rigid resource ...
This week, we are excited to kick off SQLCon 2026 alongside FabCon in Atlanta. Bringing these SQL and Fabric communities together creates a unique opportunity to learn, connect, and share what’s next ...
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(TM) 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, ...
Two zero-day flaws in the form of a denial of service (DoS) issue in .NET and an elevation of privilege (EoP) issue in SQL Server top the agenda for security teams in Microsoft’s latest monthly Patch ...
In this tutorial, we build an elastic vector database simulator that mirrors how modern RAG systems shard embeddings across distributed storage nodes. We implement consistent hashing with virtual ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Agent workflows make transport a first-order ...
CISA ordered U.S. government agencies on Thursday to secure their systems against a critical Microsoft Configuration Manager vulnerability patched in October 2024 and now exploited in attacks.
Alibaba Tongyi Lab research team released ‘Zvec’, an open source, in-process vector database that targets edge and on-device retrieval workloads. It is positioned as ‘the SQLite of vector databases’ ...
A new open-source framework called PageIndex solves one of the old problems of retrieval-augmented generation (RAG): handling very long documents. The classic RAG workflow (chunk documents, calculate ...