Part 3 Deployment and ethical considerations
This final section focuses on the practical aspects of deploying generative AI applications and the ethical considerations involved. It provides a comprehensive guide to application architecture, scaling up for production, and the operational best practices for deployment. The closing chapters emphasize the importance of ethical principles, discussing potential risks, responsible AI lifecycle, and tools for ensuring ethical AI practices.
Chapter 10 discusses the architectural considerations necessary for building generative AI applications. It covers the orchestration and grounding layers and how to filter models and responses to effectively ensure optimal application performance.
Chapter 11 focuses on the challenges of scaling generative AI applications and provides best practices for production deployment. It addresses critical aspects such as metrics, latency, scalability, and security considerations to ensure smooth and efficient operation.
Chapter 12 explains how to evaluate and benchmark large language models, discussing various metrics and benchmarks. It covers task-specific benchmarks and the importance of human evaluation in assessing model performance.
Chapter 13, the final chapter, highlights generative AI’s ethical challenges and risks. It outlines the principles and practices for responsible AI use, including content safety, data privacy, security considerations, and the ethical lifecycle of AI implementation.