Understanding Large Language Models

If you are reading this book, you have probably explored the realm of large language models (LLMs) and already recognize their potential applications as well as their pitfalls. This book aims to address the challenges LLMs face and provides a practical guide to building data-driven LLM applications with LlamaIndex, taking developers from foundational concepts to advanced techniques for implementing retrieval-augmented generation (RAG) to create high-performance interactive artificial intelligence (AI) systems augmented by external data.

This chapter introduces generative AI (GenAI) and LLMs. It explains how LLMs generate human-like text after training on massive datasets. We’ll also overview LLM capabilities, limitations such as outdated knowledge potential for false information, and lack of reasoning. You’ll be introduced to RAG as a potential solution, combining retrieval models using indexed data with generative models to increase...