AI Engineering: Building Applications with Foundation Models

I'm only up to Chapter 4, and this book is fantastic! I'm coming from a ML/deep learning background, looking to level up with generative AI and LLM's, and I think this book is great! I was hesitant at first, there is so much to find for free - but this book is concisely pulling it together with many interesting details! If I had been bouncing around on the web instead of reading this book, I don't think I'd know 1/2 as much about these early chapter topics as I do now! The book is getting me excited about working in the field - building an AI based product, leveraging existing models, digging into foundation model training - and there's still 7 more chapters to go!

This is an amazing book. I'm reading this bible every day.Big thanks to the author.

It comprehensively introduces the basic knowledge of AI.

Great comprehensive book on AI engineering. This book simplifies the concepts and techniques of advanced AI development with practical applications across Generative AI

Awesome book. The author thoroughly explained every topic discussed. Being in a masters program now this book goes even deeper into some of the trends and algorithms than my professors.

In academia, there is the concept of a "review article" -- it summarizes and organizes the major research findings into a framework that makes it easy to come up to speed on a topic. Frequently, the review articles themselves end up defining the area, and this is what Chip Huyen manages to achieve in this comprehensive book. The quality of the writing and diagams are uniformly high -- Chip uses simple language to great effect.I think of myself as being somewhat up to date, but I have learned something new every chapter and not just minor details. For example, I had missed the Deep Mind paper pointing to "self-delusion" as the reason for hallucinations. Chip provides a clear explanation and shows an example. This fundamentally affects my intuitive understanding of model errors.Of course, there's a danger with writing a review of a fast moving field. Just today, DeepSeek published an article showing that they can avoid SFT altogether and do just train a model on preferences, alphago-style. If this takes off, Chapter 7 will need a second edition.Strongly recommend this book. It's invaluable for anyone building applications using GenAI models.

Good booj

Chip Huyen has done it again—delivering a smart, thorough guide that takes readers step by step through complex material with remarkable clarity. Through simple, accessible examples, she empowers readers to achieve their goals. The modular structure allows experienced readers to navigate at their own pace, while her unmatched coverage of practical applications sets this work apart.Her approachable tone builds reader confidence, ensuring full comprehension of the material. Well-documented and diverse sources provide a robust foundation, while her presentation style—concise, clear, and thoughtfully structured with short, easy to digest paragraphs—creates an ideal learning experience. Important points and deeper insights are segregated and clearly marked for easy reference.This resource will undoubtedly become a valued reference, likely to evolve alongside the field itself. Thank you, Chip! A worthy successor to your first volume -- and we eagerly await your next contribution to the field. ~ Denise Shekerjian, author Uncommon Genius (Viking, Penguin)