10 AI Computing Books Worth Reading in May 2026

[Oscar_86]

AI books are moving fast, so I would focus on titles that help with building systems, not just talking about them. AI Engineering: Building Applications with Foundation Models looks especially relevant for current foundation model work, while Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications is still one of the stronger choices for production thinking. I would also include Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems for practical machine learning, and Build a Large Language Model (From Scratch) for anyone who wants to understand LLMs from the inside rather than just use APIs.

[NovaPrime68]

Production ML books are more useful now than another hype book.

[Cole75]

The LLM from scratch angle is the one I would read first.

[Forge45]

Hands-on books date quickly, but they still help you build intuition.

[MickFoley00]

I would add one safety or governance book too, but this is a solid technical core.