VAST AI OS will leverage NVIDIA libraries to accelerate both compute and data services for RAG, vector search, real-time SQL, ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

Building retrieval-augmented generation (RAG) systems for AI agents often involves using multiple layers and technologies for structured data, vectors and graph information. In recent months it has ...

Databricks, Snowflake, Amazon Redshift, Google BigQuery, and Microsoft Fabric – to see how they address rapidly evolving ...

The open source MySQL spin-off has steadily added features all its own. Here are five good reasons to switch to MariaDB.

SQL will continue to serve as the lingua franca but the world of data will speak in graphs, vectors, LLMs too– and relational databases will stay but not in the same chair. Here’s why?

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 ...

AI’s next leap won’t come from bigger models or longer context windows, but from better-organized knowledge.

Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower ...

Why Most Retrieval-Augmented Generation Systems Fail Online Retailers — And the Practical Fixes That Turn Customer Interactions Around ...