Artificial Intelligence: Foundations and Concepts

One brisk morning in 1936, an unassuming English mathematician named Alan Turing found himself scribbling equations on a piece of paper, deeply lost in thought. Little did he know that his silent meditations would one day ripple across the globe, reshaping how humanity perceives consciousness and intelligence. Turing’s question—“Could a machine ever think?”—wasn’t merely academic. In his quest to decipher the mechanics of the human mind, he inadvertently paved the way for a revolution in computing that would unravel codes during World War II, save countless lives, and ultimately bring the entire world face-to-face with the startling possibilities of artificial thought.
Fast-forward to 1956, when a bright-eyed American computer scientist named John McCarthy invited a handful of luminaries to a workshop at Dartmouth College. They collectively christened the field “Artificial Intelligence,” charting a course that would catapult Turing’s foundational ideas into the realm of serious scientific inquiry. This small gathering—just a handful of curious minds in a modest lecture hall—ignited a transformation that has arguably become as significant as the Industrial Revolution or the dawn of the Internet. AI promised machines that could learn, reason, and adapt much like humans, if not better.
However, if we zoom out even further, we notice that the dream of mechanical minds is much older. Mythologies and legends from around the world flirt with the notion of artificial beings. From the Greek tale of Talos, the giant bronze automaton, to medieval stories of golems molded from clay, humans have long been captivated by the possibility of imbuing inanimate objects with life—or something resembling life. The difference is that Turing and McCarthy moved these ancient reveries from fable to framework. They gave AI the mathematical language it needed to step out of myth and into everyday reality.