InfoWorld

How to build RAG at scale

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform discipline. Enterprises that succeed with RAG rely on a layered architecture.
Geeky Gadgets

How to build a Retrieval-Augmented Generation (RAG) system

Retrieval-Augmented Generation (RAG) systems have emerged as a powerful approach to significantly enhance the capabilities of language models. By seamlessly integrating document retrieval with text ...

Karpathy shares 'LLM Knowledge Base' architecture that bypasses RAG with an evolving markdown library maintained by AI

Karpathy proposes something simpler and more loosely, messily elegant than the typical enterprise solution of a vector ...
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 ...
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 ...
Forbes

Prompting, Fine-Tuning, RAG And AI Agents For Future Marketing

Prof. Aleks Farseev is an entrepreneur, keynote speaker and CEO of SOMIN, a communications and marketing strategy analysis AI platform. Large language models, widely known as LLMs, have transformed ...