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 ...

If you are interested in learning more about how to use Llama 2, a large language model (LLM), for a simplified version of retrieval augmented generation (RAG). This guide will help you utilize the ...

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...

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 ...

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 ...

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used ...

What is Retrieval-Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is an advanced AI technique combining language generation with real-time information retrieval, creating responses ...

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 ...

URL structure has always been an important SEO factor to align relevancy, but now they can also influence AI retrieval. Learn ...