Introduction to AI
Mustapha El Moussaoui · 2026
This chapter provides a conceptual overview of Artificial Intelligence, clarifying its mechanisms and dispelling popular myths. Rather than functioning as an “artificial brain,” AI is characterized as an “engine of inference,” a system that learns patterns and correlations from vast datasets. The discussion situates AI within a historical trajectory, tracing antecedents from Leibniz’s dream of a universal calculus to Babbage’s Analytical Engine, and from symbolic AI and expert systems to the emergence of machine learning and neural networks. The chapter highlights the breakthroughs that enabled modern AI, including backpropagation, deep learning, and landmark architectures such as Convolutional Neural Networks and Generative Adversarial Networks. The role of Alan Turing’s reframing of intelligence as performance is emphasized, as is the paradigm shift from rule-based programming to data-driven learning. The chapter concludes by explaining generative “hallucination” as the statistical recombination of patterns rather than reasoned design, setting the stage for the book’s central concern: how architects can direct and discipline this hallucinatory capacity.