ABSTRACT: I present a discussion of the basic aspects of the well-known problem
of prediction and inference in physics, with specific attention to the role of models, the use
of data and the application of recent developments in artificial intelligence. By focusing in
the time evolution of dynamic system, it is shown that main difficulties in predictions arise
due to the presence of few factors as: the occurrence of chaotic dynamics, the existence
of many variables with very different characteristic time-scales and the lack of an accurate
understanding of the underlying physical phenomena. It is shown that a crucial role is
assigned to the preliminary identification of the proper variables, their selection and the
identification of an appropriate level of description (coarse-graining procedure).
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