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23 de feb. de 2022 · As part of Meta AI’s Inside the Lab event on February 23, 2022, LeCun is sketching an alternate vision for building human-level AI. LeCun proposes that the ability to learn “world models” — internal models of how the world works — may be the key. Meta AI is sharing some of LeCun’s ideas in brief here, including his proposal for a ...
Yann LeCun has been associate editor of PLoS ONE (2008-2011), IJCV (2003-2007), IEEE Trans. PAMI (2003-2005), Pattern Recognition and Applications, Machine Learning Journal (1996-1998), IEEE Transactions on Neural Networks (1990-1991).
杨立昆 （法語： Yann Le Cun ，原中文譯名 扬·勒丘恩 ，1960年7月8日 — ）是一名 法国 计算机科学家 ，2018年 图灵奖 得主，他在 机器学习 、 计算机视觉 、 移动机器人 （英语：Mobile robot） 和 計算神經科學 等领域都有很多贡献。. 他最著名的工作是在 光学字符 ...
Yann Le Cun [ləkœ̃] 1, né le 8 juillet 1960 à Soisy-sous-Montmorency 2, est un chercheur en intelligence artificielle et vision artificielle (robotique) français. Il est considéré comme l'un des inventeurs de l' apprentissage profond 3. Il reçoit le prix Turing 2018, le 27 mars 2019, partagé avec Yoshua Bengio et Geoffrey Hinton .
Yann LeCun Courant Institute of Mathematical Sciences, New York University yann@cs.nyu.edu Meta - Fundamental AI Research yann@fb.com June 27, 2022 Abstract How could machines learn as e ciently as humans and animals? How could ma-chines learn to reason and plan? How could machines learn representations of percepts
Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department.
of handwritten digits Yann LeCun, Courant Institute, NYU Corinna Cortes, Google Labs, New York Christopher J.C. Burges, Microsoft Research, Redmond The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST.
