InfoWorld

Surveying the LLM application framework landscape

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...
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 ...
ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
VentureBeat

Vectara raises $25M as it launches Mockingbird LLM for enterprise RAG applications

Vectara, an early pioneer in Retrieval Augmented Generation (RAG) technology, is raising a $25 million Series A funding round today as demand for its technologies continues to grow among enterprise ...
TechRepublic

Retrieval Augmented Generation: What It Is and Why It Matters for Enterprise AI

Retrieval Augmented Generation: What It Is and Why It Matters for Enterprise AI Your email has been sent DataStax's CTO discusses how Retrieval Augmented Generation (RAG) enhances AI reliability, ...
ZDNet

RAG can make AI models riskier and less reliable, new research shows

Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...