eWeek

What is Retrieval-Augmented Generation? How it Works & Use Cases

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
Geeky Gadgets

Google’s Embedding Gemma On-Device RAG Made Easy for NLP Efficiency

What if the power of advanced natural language processing could fit in the palm of your hand? Imagine a compact yet highly capable model that brings the sophistication of retrieval augmented ...
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 ...
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 ...
Statetechmagazine

What Is Retrieval Augmented Generation, and How Are State and Local Agencies Using It?

RAG allows government agencies to infuse generative artificial intelligence models and tools with up-to-date information, creating more trust with citizens. Phil Goldstein is a former web editor of ...
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 ...