Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...
Qdrant develops a vector search engine designed for production AI systems, enabling teams to configure retrieval, ranking, and filtering to support scalable applications such as semantic search and AI ...
While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as muc ...
SQL Server 2025: Redefining the modern data platformIssued by Ascent TechnologyJohannesburg, 11 Mar 2026 SQL Server 2025: Redefining the modern data platform. Explore how SQL Server 2025 reshapes the ...
Process Diverse Data Types at Scale: Through the Unstructured partnership, organizations can automatically parse and transform documents, PDFs, images, and audio into high-quality embeddings at ...
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 ...
Endee.io launches Endee, an open source vector database delivering fast, accurate, and cost-efficient AI and semantic search at scale. Endee rethinks vector DBs for high recall, low latency, and low ...
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, ...
This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. Every enterprise IT executive faces the same AI paradox: their most valuable data sits ...
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