Cutting RAG inference costs 6x starts with deciding what never reaches the LLM

Here is what changes when you cannot afford to be probabilistic about everything, and how a cascade architecture solves it.
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 ...
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 ...
Web CMS

Improving Gen AI Accuracy With Retrieval Augmented Generation

Generative artificial intelligence is transforming publishing, marketing and customer service. By providing personalized responses to user questions, generative AI fosters better customer experiences ...
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 ...