Video Generation with AI

Preface

Video generation is advancing at a remarkable pace. New models and techniques appear almost monthly, each improving realism, consistency, and multimodal reasoning. Yet often the difficult part is not using these models. It is understanding why they work.

I wrote this book because I believe that real understanding comes from connecting theory with implementation. Reading a paper is valuable. Building a model is valuable. The greatest insight comes from understanding how the architecture, training process, and engineering decisions fit together to produce the final result.

This is not a catalog of every video generation model or a survey of every research paper. The field is moving too quickly for that. Instead, this book focuses on the core ideas that appear across modern systems and explains them through practical examples and working implementations.

My hope is that this book helps the next generation of builders move beyond treating these models as black boxes and gives them the foundation to build what comes next.

Who Should Use This Book

This book is intended for software developers, machine learning engineers, AI researchers, data scientists, and technical architects who want to understand how modern video generation systems are designed, trained, and deployed.

It assumes a basic familiarity with Python and machine learning concepts but does not require prior experience with video generation. By connecting theory with implementation, the book aims to help you understand ...