The Logic and the Ledger: Tracing the DNA of AI

Abstract

The development of intelligent systems is fundamentally and inseparably linked to a sophisticated

mathematical framework. Modern artificial intelligence (AI), particularly its subfields of machine learning

(ML) and deep learning, is not a new discipline of computer science but rather a highly advanced

application of classical and novel mathematical principles. The models and algorithms that enable systems

to process data, learn intricate patterns, and optimize predictions are built upon a bedrock of abstract

mathematical theories. This paper systematically deconstructs this relationship, demonstrating how core

mathematical disciplines serve as the language, the engine, and the conceptual framework for all

intelligent systems. The analysis will traverse from foundational principles to their application in

cutting-edge architectures and conclude with a discussion of the theoretical and practical challenges that

are currently shaping the future of the field.