In some sports, coaches appoint impact playersplayers whose entry onto the field during the match can tip it over. In science too, there are “impact” players. Gaël Varoquaux, computer scientist at the National Institute for Research in Digital Sciences and Technologies (Inria), is perhaps one of them. In addition, he is sporty, a federal sailing instructor since he was 18, a cross-country skier and a fan of climbing and long bike rides.
At 43, he is above all the most cited French researcher in the field of artificial intelligence (AI). An article that he co-signed in 2011 is mentioned more than 62,000 times in other works, according to the Scopus database, while those of Yann Le Cun, another national star in the field, are mentioned a maximum of 60,000 times.
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However, his contribution is not linked to generative AI like ChatGPT or even deep learning, which has revolutionized image recognition. This is machine learning, the use of which he helped to facilitate by being co-author of the most widely used software in this area, Scikit-learn. This toolbox is packed with more than 150 statistical methods to classify objects, group them by similarity or identify their particularities automatically. Everything you need to talk about large masses of data, in just a few lines of code. Scikit-learn is downloaded around 80 million times per month, while the deep learning tools, PyTorch or TensorFlow, from the giants Meta and Google, are downloaded less than 30 million times, Gaël Varoquaux recalled during a presentation at the dotAI conference, October 18, in Paris.
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