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 ...

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 ...

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 ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

In the era of generative AI, large language models (LLMs) are revolutionizing the way information is processed and questions are answered across various industries. However, these models come with ...

Widespread amazement at Large Language Models' capacity to produce human-like language, create code, and solve complicated ...

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 ...

The adoption of AI tools is accelerating across the economy, with 39% of UK organizations already using the technology. Across industries – from finance and healthcare to manufacturing and retail, 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 ...