Informaticien théorique britannique, Leslie Valiant a été primé de nombreuses fois : il a notamment reçu le Prix Turing en 2010. Il enseigne à Harvard depuis 1982, et est le titulaire de la chaire Thomas Jefferson Coolidge en informatique théorique et mathématiques appliquées de la faculté d’ingénierie et de sciences appliquées (Harvard School of Engineering and Applied Sciences).
Title: What can be automated: A Viewpoint from Learning and Evolution
Abstract: With machine learning technology we are now able to automate many tasks that humans learn to perform through experience rather than through step-by-step instruction. Without such a learning capability we are limited to automating tasks for which a step-by-step sequence of instructions is known. In this talk we shall ask whether it is possible to circumscribe the set of tasks that we can expect to effectively automate. The discussion will start from the hypothesis that all the information that resides in living organisms was initially acquired either through learning by an individual or through evolution. Then any unified theory of evolution and learning should be able to characterize the capabilities that humans and other living organisms can potentially acquire and perform. These tasks then comprise feasible targets for automation. We shall discuss where we are with such a unified theory.