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Abstract
I will discuss Positive Distribution Shift as a major paradigm that drives modern machine learning, and that should be formulated, studied and understood. This will be a mostly speculative talk posing questions rather than giving answers. The talk is based on work of others in and outside the collaboration as well as ongoing discussions and work in progress.