Traditional RAG typically retrieves relevant text from a vector database and supplies it to an LLM as context. Automation ...

FlureeDB acts as a secure context layer fit for autonomous systems: pull from many data sources wherever they live, answer structured queries ...

There’s been a debate of sorts in AI circles about which database is more important in finding truthful information in generative AI applications: graph or vector databases. AWS decided to leave the ...

Wikidata has built the semantic web backbone supporting knowledge cards in popular engines. Now, it's extending this foundation using a vector database to enhance its existing knowledge graph and ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Oracle Corp.’s flagship database management system is now available as a cloud service. Oracle Database 23ai features vector search and more than 300 additional major features, with many focused on ...

Artificial Intelligence (AI) agents based on Retrieval-Augmented Generation (RAG) technology are rapidly proliferating. RAG ...

Google is hosting a version of its Cloud Next conference in Tokyo this week, and it’s putting the focus squarely on tweaking its databases for AI workloads (because at this point in 2024, AI is the ...

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

A VB Pulse survey of 101 enterprises finds 57% traced a wrong AI agent answer to bad context, and only 25% have a governed context layer in production.