Does AI have to be complex?

To celebrate the start of the 21st century, the renowned journal *Nature* unveiled a list of the ten most-cited scientific articles in the world. Four of them directly concern artificial intelligence, and at the top of the list is “Deep Residual Learning for Image Recognition,” better known as ResNet. What’s surprising is that this seminal paper is not, technically speaking, extremely complex. And yet, it has revolutionized—and continues to revolutionize—AI research and paved the way for countless advances.

So, does AI have to be complex to be revolutionary? During this conference/debate, we’ll delve into the content of this article, examine the progress it has enabled, and then open the floor to a discussion with the audience on the major questions—both technical and philosophical—that it naturally raises.

The presentation and discussion will feature two experts: Clément Carré (founding president of Bionomeex—a doctor specializing in statistical learning) and Jean Gabriel Ganascia.