What this book covers

Chapter 1, Introduction to Generative AI Patterns, provides an overview of generative AI concepts, architectures, and their potential impact on application development.

Chapter 2, Identifying Generative AI Use Cases, guides readers through the process of identifying and evaluating potential use cases for generative AI across various domains.

Chapter 3, Designing Patterns for Interacting with Generative AI, explores different strategies for effectively communicating with and leveraging generative AI models in applications.

Chapter 4, Generative AI Batch and Real-Time Integration Patterns, discusses the different approaches for integrating generative AI into both batch-processing and real-time systems.

Chapter 5, Integration Pattern: Batch Metadata Extraction, demonstrates how to implement generative AI to extract metadata from large datasets in batch mode.

Chapter 6, Integration Pattern: Batch Summarization, covers techniques for using generative AI to create summaries of large volumes of text data.

Chapter 7, Integration Pattern: Real-Time Intent Classification, shows how to implement generative AI to classify user intents in real-time applications.

Chapter 8, Integration Pattern: Real-Time Retrieval Augmented Generation, explores advanced techniques for building question-answering systems using generative AI and retrieval augmented generation.

Chapter 9, Operationalizing Generative AI Integration Patterns, provides guidance on deploying, monitoring, and maintaining generative AI systems in production environments.

Chapter 10, Embedding Responsible AI into Your GenAI Applications, addresses ethical considerations and best practices for responsible use of generative AI in applications.