preface
The term “digital twin” has been applied to many different kinds of systems. From its origins in product lifecycle management in the early 2000s to today’s sophisticated, photorealistic, and physically accurate replicas powered by GPU-accelerated simulation and AI, the label has been applied to many different types of systems. Despite this, the core building blocks remain the same—you create a digital representation of a physical system, keep it synchronized with real world changes, and use it to make better decisions. This book describes the journey you will follow when you decide that building a digital twin will deliver real value.
As AI increasingly shapes our world, digital twins have become more important than ever. They provide the structured, up-to-date context grounded in reality that our models need to reason about real-world systems. Without that grounding, even the most advanced AI will struggle to move from generic outputs to meaningful, actionable insights.