Artificial intelligence and innovation - Definitions and principles

Since the mid-2010s, advances in artificial intelligence (AI) have been undergoing constant and often exponential development. The fascination with these techniques transcends scientific, economic and political boundaries, as evidenced by the growing number of academic publications, popularization articles and numerous essays and dossiers devoted to the subject.

Although AI is now a flagship technology of the 21st century, its theoretical foundations date back to the 1950s, when mathematician Alan Turing laid the foundations for the first concepts of artificial intelligence. It is the result of the slow construction of concepts and algorithms that the growing availability of data and the steady increase in computing ressources have made concretely feasible.

This fast-growing field encompasses a set of complex algorithms enabling machines to solve problems, learn from experience and optimize their performance autonomously.

In this article, geared primarily to engineering students and, more generally, anyone wanting a first introduction to the subject, we offer a summary that aims to briefly retrace the history of AI, define its key concepts and outline the main learning methods. Each technique will be illustrated with simple examples to facilitate understanding, helping to clarify the workings of this technological revolution. This article is associated with companion articles [AG 297] and [AG 298] which looks at the applications of these techniques and the innovations they enable in a wide range of fields.

Readers will find these references in the "Further reading" section of this article. An additional bibliography and links to websites provide useful resources for furthering knowledge on the subject.