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

The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via ...
VentureBeat

Why enterprise RAG systems fail: Google study introduces 'sufficient context' solution

A new study from Google researchers introduces "sufficient context," a novel perspective for understanding and improving retrieval augmented generation (RAG) systems in large language models (LLMs).
Forbes

Pure Storage Builds LLM RAG Pipeline, Gains Nvidia OVX Certification

For generative AI to live up to its promise of transforming the enterprise, it first needs to meet the needs of the enterprise. Large language models need business-specific context to minimize ...
InfoWorld

How to run RAG projects for better data analytics results

RAG can make your AI analytics way smarter — but only if your data’s clean, your prompts sharp and your setup solid. The arrival of generative AI-enhanced business intelligence (GenBI) for enterprise ...
Finextra

5 high-ROI uses of RAG models in banking and fintech

General purpose AI tools like ChatGPT often require extensive training and fine-tuning to create reliably high-quality output for specialist and domain-specific tasks. And public models’ scopes are ...
InfoWorld

How to create your own RAG applications in R

See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to use an LLM to extract structured data for text filtering. One of the ...
Security Boulevard

How Escape AI Pentesting Exploited SSRF in LiteLLM

The post How Escape AI Pentesting Exploited SSRF in LiteLLM appeared first on Escape – Application Security & Offensive Security Blog. At Escape, we routinely test the AI infrastructure that teams ...