AI Engineering. Building Applications with Foundation Models

Foundation models have enabled many new Al use cases while lowering the barriers to entry for building Al products. This has transformed Al from an esoteric discipline into a powerful development tool that anyone can use - including those with no prior Al experience. In this accessible guide, author Chip Huyen discusses Al engineering : the process of building applications with readily available foundation models.
Al application developers will discover how to navigate the Al landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of application patterns. The book also introduces a practical framework for developing an Al application and efficiently deploying it. Understand what Al engineering is and how it differs from traditional machine learning engineering. Learn the process for developing an Al application, the challenges at each step, and approaches to address them.
Explore various model adaptation techniques, including prompt engineering, RAG, finetuning, agents, and dataset engineering, and understand how and why they work. Examine the bottlenecks for latency and cost when serving foundation models and learn how to overcome them. Choose the right model, metrics, data, and developmental patterns for your needs.