Geeky Gadgets

AI Retrieval Augmented Generation (RAG) explained by IBM

Retrieval Augmented Generation (RAG) is a groundbreaking development in the field of artificial intelligence that is transforming the way AI systems operate. By seamlessly integrating large language ...
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

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 ...
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 ...
Wired

Reduce AI Hallucinations With This Neat Software Trick

If you’ve ever used a generative artificial intelligence tool, it has lied to you. Probably multiple times. These recurring fabrications are often called AI hallucinations, and developers are ...
InfoQ

Reducing False Positives in Retrieval-Augmented Generation (RAG) Semantic Caching: a Banking Case Study

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
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 ...