Part 2 Advanced techniques and applications
This section delves deeper into more advanced techniques and specific applications of generative AI. It covers prompt engineering, retrieval-augmented generation (RAG), and vector databases for data retrieval. Additionally, it explores model adaptation and fine-tuning, providing readers with the knowledge to customize and optimize generative AI models for specific tasks.
Chapter 6 explores prompt engineering in detail, emphasizing its importance in improving the performance of generative AI models. The chapter discusses various techniques and best practices to craft effective prompts.
Chapter 7 introduces RAG, explaining how it combines retrieval mechanisms with generative models to enhance information accuracy and relevance. The chapter discusses the architecture, implementation challenges, and strategies for effective use.
Chapter 8 focuses on integrating generative AI with data retrieval systems using vector databases. It provides insights into implementing chat interfaces that efficiently interact with and retrieve data.
Chapter 9 explores the processes of model adaptation and fine-tuning, offering a detailed guide on customizing generative AI models to better suit specific tasks and applications. It includes best practices and practical examples.