Artificial intelligence and innovation - Applications

One of the most promising technologies of the 21st century, artificial intelligence (AI) opens the way to automating a variety of processes that we humans perceive as intelligent: deducing, learning, reading, imagining, speaking, recognizing, composing, writing, cooperating, solving, exploring, etc. ... and even lying! The latest advances in AI demonstrate formidable capabilities with many potential applications, such as the ability to predict a phenomenon or train for a task, for example. While the general public may have heard of machine learning (ML) techniques – and, in particular, artificial neural networks –, which have seen dazzling development and success in recent years, AI is not limited to this single approach and exploits a wide variety of methods. It is part of a broader field, the digital sciences, in particular computer science and mathematics, whose advances feed it: by relying on algorithms capable of learning from data, these techniques are profoundly transforming many sectors. From industry to agriculture, science, energy, transport and even the arts. Supervised, unsupervised and reinforcement learning, described briefly in a companion article to this one [AG 296] , are at the heart of this revolution. The strength of these techniques lies in their unique ability to integrate multivariate data from heterogeneous sources, identify non-linear relationships and reveal dynamics that traditional approaches, such as numerical simulation, struggle to grasp.

These technologies do more than simply complement existing methodologies: they are profoundly transforming the way in which contemporary problems are tackled. In the basic sciences, for example, AI enables the processing of immense volumes of experimental data, as in particle physics or astronomy, where predictive models identify rare or unexpected phenomena. In industry, ML optimizes manufacturing processes, enabling greater personalization and lower energy costs. In agriculture, intelligent algorithms analyze satellite images and weather data to predict yields and optimize the use of resources. The healthcare sector is also seeing a paradigm shift: AI is contributing to early disease diagnosis, precision medicine and the discovery of new treatments. Finally, in economics, sophisticated predictive models are helping to anticipate financial crises and optimize global supply chains. These and many other applications, explored in this article, illustrate a breakthrough: AI doesn't just improve what...