We celebrate knowledge, build machines of dazzling complexity, and unlock the secrets of nature. Yet the vastness of what we do not know still dwarfs our achievements. The new Theory of Nescience invites readers on a journey not through what is known, but into the very depths of ignorance itself.

At its core lies a radical idea: perfect knowledge implies randomness. From this insight emerges a rigorous mathematical framework (grounded in the principles of computability, complexity, and artificial intelligence) that enables us to measure ignorance, evaluate scientific progress, and guide research toward a deeper understanding of the unknown unknowns, the deeper mysteries we have not even imagined.

But this is not merely a theoretical pursuit. The theory presented here is not only elegant, it is practical. It offers concrete tools to confront some of the most challenging open problems in science and technology, to extract meaning from data, and to uncover discoveries beyond the reach of intuition alone.

Whether you're building advanced systems or grappling with foundational questions, this book offers a new lens for understanding how knowledge is acquired, structured, and ultimately constrained. It's not about knowing more, it's about better understanding what we don't know.