Architectural patterns for graph-enhanced RAG: Moving beyond vector search in production

Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private ...

The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next

Vector database pioneer Pinecone recognizes this and is pivoting to meet the specific needs of agentic AI. The company today ...
Visual Studio Magazine

Building AI-Powered Applications with Azure Database for PostgreSQL

Jean Joseph, a data & AI engineer with deep expertise in database development, will explain how to build AI-powered applications with Azure Database for PosgreSQL at at upcoming developer conference.
dbta

Beyond RAG basics: Strategies and best practices for implementing RAG

Join DBTA and Elastic as we explore advanced techniques in retrieval augmented generation (RAG). This talk provides developers, data scientists, and AI enthusiasts with essential insights to elevate ...
Visual Studio Magazine

SQL Database in Microsoft Fabric in Preview for Faster AI Apps

Microsoft's early embrace of advanced AI in its dev tooling continues apace with the new public preview of SQL database in Microsoft Fabric, the company's analytics/data platform. Fabric is a ...
InfoWorld

MongoDB releases mongot source code to boost RAG and AI workloads

MongoDB has released the source code of mongot, the engine that powers MongoDB Search and Vector Search, under the Server Side Public License. Analysts say the move would help developers of the ...