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 ...
Unite.AI

AI Pollution in Search Results Risks ‘Retrieval Collapse’

As AI content pollutes the web, a new attack vector opens in the battleground for cultural consensus. Research led by a Korean search company argues that as AI-generated pages encroach into search ...
InfoWorld

Addressing AI hallucinations with retrieval-augmented generation

The hallucinations of large language models are mainly a result of deficiencies in the dataset and training. These can be mitigated with retrieval-augmented generation and real-time data. Artificial ...
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 ...
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 ...
Forbes

The Power Of RAG: How Retrieval-Augmented Generation Enhances Generative AI

Rahul is the Chief Product and Marketing Officer for Innodata, a global data engineering company powering next-generation AI applications. Generative AI is transforming industries and lives. It ...