A study on vector database and AI integration identifies unstable indexing, weak cross-modal fusion, and rigid resource ...
Heterogeneous NPU designs bring together multiple specialized compute engines to support the range of operators required by ...
A Scottish startup developing free-space optics completed tests where it used a crystal-based laser to transmit data across ...
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the ...
Recent SQL Server 2025, Azure SQL, SSMS 22 and Fabric announcements highlight new event streaming and vector search capabilities, plus expanding monitoring and ontology tooling -- with tradeoffs in ...
Retrieval-Augmented Generation (RAG) is critical for modern AI architecture, serving as an essential framework for building ...
Modern semantic search does not have to require a separate vector database. Data architects, database engineers, developers, or platform leaders can integrate Vertex AI and Cloud SQL vector indexes ...
Open-source platform with 30+ MCP tools lets AI agents autonomously create pipelines, query databases, search vector ...
AI database innovation at Oracle drives a redesigned data platform with vector search, AI agents, stronger privacy controls ...
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 ...
Nvidia "GeForce Evangelist" Jacob Freeman spoke with YouTuber Daniel Owen late last week about the company's new DLSS 5 technology. He explained a little more about how the tech works, its limitations ...
TL;DR: KIOXIA's AiSAQ technology, combined with NVIDIA's cuVS Library, enables efficient scaling of high-dimensional vector searches to 4.8 billion vectors on a single server, achieving up to 20X ...
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