The theoretical basis for computer science and related technologies of our days was already laid down in the 1930s and 1940s, mainly by four scientists: John von Neumann, Claude Shannon, Norbert Wiener and Alan Turing. Working at Bletchley Park, the legendary codebreaking centre, Turing was one of the team to break German military ciphers during World War Two. Turing became one of the most influential scientists in the 20th century for his achievement in the research of artificial intelligence, for the Turing machine and the Turing test, and his seminal work on the foundation of morphogenesis.

In 1936 Turing, who was working on logic and probability at the time, formulated a very important question: is there, even if only in theory, a method or algorithm that can be used to compute all mathematical problems? Through the analysis of logic-based procedures performed by human beings, and the analysis of the operation of a hypothetical computer, he arrived at the conclusion that there was no such algorithm. It was also in 1936 that the American logician, Alonzo Church formulated his thesis, equivalent of Turing’s, stating: “there is no method to make a distinction between theses in number theory and statements that are not theses”. This is why the thesis is called the Church-Turing thesis.

The author of the paper “On computable numbers” went beyond the mathematical problem, and generalising it, he strived to achieve a synthesis of logical and physical processes, thinking and action. Turing’s theory of the Universal Turing Machine was intended for this end. He envisaged an automaton, a simple computer model that consisted of three parts or internal states: memory and a set of instructions, a head and an infinitely long (input) tape divided into cells. The function of input symbols is determined by rules, then the machine prints new signs (standardised instructions encoded in numbers) on the tape. Anything could be computed provided that the strip of tape is long enough. But how can one systemise, what are the rules for segments of reality (human intuition, etc.) that can be described only with difficulty, if at all, by mathematical models. Turing attempted to provide an answer in a paper published in 1938, however, he never again resumed to elaborate on this question.

In the 1940s Turing worked on turning his theoretical computer into practical reality. He was no longer interested in what the Turing machine was not able to do, but was engaged in exploring its potentials. It is like “building a brain”, he stated. He envisaged that AI (artificial intelligence) might possibly be created by the turn of the millennium, and would pass the Turing Test, which measures machine intelligence (1950). He also published an article on learning, which has become a significant element in AI research today. Drawing on the findings of neurology and physiology of his time, Turing drew up a theory that suggested neural networks: if a mechanical system is complex enough, it may as well possess the ability to learn.