Introduction to Generative AI, Second Edition

Generative AI is more than a set of clever prompts or impressive demos. In Introduction to Generative AI, Second Edition, Numa Dhamani and Maggie Engler explain the technology behind large language models while keeping its real-world consequences in view. The result is a wide-ranging introduction to how these systems work, where they are being used, and why responsible use requires more than technical know-how.

From language models to AI agents

The book begins with the foundations: the evolution of language processing, how large language models are trained, and what they can—and cannot—do. It goes on to explore multimodal systems, reasoning models, model efficiency, and the techniques used to refine AI outputs. Later chapters introduce prompt engineering and autonomous agents, including how agents operate and the risks that come with greater autonomy and access to tools.

The questions behind the technology

Technical developments sit alongside the issues they raise. The authors examine training-data bias, privacy and data protection, synthetic media, copyright and creator rights, adversarial attacks, hallucinations, and the challenges of evaluating AI systems. This perspective helps connect the mechanics of generative AI with questions that matter to people building, adopting, or simply making sense of it.

AI at work and in society

Examples and discussions span professional work, education, creative industries, daily life, and the economy. The book also considers chatbots’ social role and the policies and practices involved in building and using AI more responsibly. Its central strength is this broader lens: generative AI is presented not as a purely technical tool, but as a technology shaped by—and affecting—human institutions and choices.

A clear starting point for curious readers

With 11 chapters moving from core concepts to applications, risks, and future questions, this second edition is suited to readers seeking a grounded overview of generative AI without needing prior technical experience. Read it to build a clearer picture of both the capabilities and the limits of today’s AI systems.