The term "Artificial Intelligence" was first used by John McCarthy, a professor at Dartmouth College (New Hampshire, United States). He defined it as "the science and engineering of making intelligent machines, especially intelligent computer programs".
This discipline, spanning mathematics, computer science and fields such as physics and electronics, has developed steadily. Today, growing computing power, the availability of ever-larger datasets and the emergence of new algorithms have placed it at the heart of the digital revolution.
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Making a prediction
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Machine learning is a subset of artificial intelligence. Arthur Samuel, a pioneer of both machine learning and computer games, described it as the "field of study that gives computers the ability to learn without being explicitly programmed to learn". As that sounds a little too "futuristic", Tom Mitchell's definition is now preferred: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E." In practice, then, the aim of a learning algorithm is to make a prediction—a value, a category and so on—for a particular context, based on prior training in that context.
