Best introductory books on artificial intelligence

This book provides a thought-provoking exploration of AI's potential long-term impact on humanity, covering ethics and future possibilities. It offers a crucial big-picture perspective on AI development and safety, essential for any introductory understanding.

This book is an excellent starting point for anyone new to AI, offering a jargon-free explanation of how AI systems work and their impact. Its recent update ensures it covers the latest trends and ethical considerations in AI, making it highly relevant for 2026.

This book provides essential hands-on knowledge for building and fine-tuning large language models using modern tools. It's ideal for developers and data scientists looking to apply LLM concepts to real-world applications effectively.

This book remains a highly practical guide for 'doing the work' in machine learning, offering a hands-on approach to training and tuning models. It's an excellent resource for those ready to move beyond theoretical concepts and gain practical experience.

This book bridges the gap from simply using LLMs to successfully deploying LLM products, covering critical aspects like retrieval, evaluation, and iteration. It's a foundational text for anyone aiming to build robust, production-ready AI applications.

This book offers an engaging and non-technical overview of crucial AI concepts, making it highly suitable for beginners. It equips readers with a fundamental understanding of AI's impact without requiring any prior technical background.

This book provides a clear and structured foundation for understanding core AI concepts without delving into complex mathematics. It's perfect for those who need to grasp the basics before exploring more advanced topics in artificial intelligence.

This book offers an accessible and engaging perspective on how algorithms influence everyday decisions across various sectors. It highlights the critical balance between algorithmic efficiency and the necessity of human judgment.

This book is a highly practical guide for daily interaction with generative AI, focusing on effective human-AI collaboration. It offers immediate insights into improving workflows and developing a clear mental model for working alongside AI.

This book is crucial for anyone looking to effectively utilize generative AI, as it focuses on designing stable and effective inputs. It provides practical guidelines for working with large language models and diffusion models, a key skill in today's AI landscape.

This book offers a hands-on path into transformers and GPT-style models, providing sufficient depth to understand their underlying mechanisms. It's perfect for those who learn best by implementing and want a deeper, practical understanding of LLM construction.