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 ...
Forbes

AI Inferencing Is Growing In Importance—And RAG Is Fueling Its Rise

As the AI infrastructure market evolves, we’ve been hearing a lot more about AI inference—the last step in the AI technology infrastructure chain to deliver fine-tuned answers to the prompts given to ...
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 ...
Finextra

What is RAG in fintech and how financial services are using it with LLMs to power AI innovation

To operate, organisations in the financial services sector require hundreds of thousands of documents of rich, contextualised data. And to organise, analyse and then use that data, they are ...