InfoWorld

Retrieval-augmented generation, step by step

RAG is a pragmatic and effective approach to using large language models in the enterprise. Learn how it works, why we need it, and how to implement it with OpenAI and LangChain. Typically, the use of ...
Forbes

Retrieval-Augmented Generation Is An Engineering Problem, Not A Model Problem

Every few months, the enterprise AI conversation resets around the same flawed premise that better models solve the problem. When large language models hallucinate, the instinct is to reach for a ...
Forbes

How Retrieval-Augmented Generation Could Solve AI’s Hallucination Problem

Large language models (LLMs) like OpenAI’s GPT-4 and Google’s PaLM have captured the imagination of industries ranging from healthcare to law. Their ability to generate human-like text has opened the ...
VentureBeat

Mistral launches API for building AI agents that run Python, generate images, perform RAG and more

The well-funded and innovative French AI startup Mistral AI is introducing a new service for enterprise customers and independent software developers alike. Mistral's Agents application programming ...
InfoWorld

Fully local retrieval-augmented generation, step by step

How to implement a local RAG system using LangChain, SQLite-vss, Ollama, and Meta’s Llama 2 large language model. In “Retrieval-augmented generation, step by step,” we walked through a very simple RAG ...