Big Data: when it is cheaper to store data than to decide what to do with it. Big Bullshit: when it is easier to spread BS than to filter it
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Brandolini *almost* figured it out with his law: "it takes 10x more effort to refute bullshit than to create it."
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He missed 2 things. 1: Bullshit presents a sorting problem (separating true and false) not a refutation problem (demonstrating falsehood)
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@vgr In the societal sense,probably a good thing for self-learning models. of course, after removing noise,overfitting and cross-validationThanks. Twitter will use this to make your timeline better. UndoUndo
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