Models excel at predicting the past. It's the future they struggle with
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This is because models are built on knowledge from the past. What if we train a model to anticipate the problems of the future?
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For images, the model could generate complex scenes by superposing different images, and train itself on it's own image generation
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sounds like yogi berra's famous insight!
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And now, when much of the past is less relevant, what?
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Meaning all a model can know are just... Noise?
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We need a test set for every kind of statistical modeling
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Simulation modeling
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Predicting the future accurately needs a hell lot of intelligence.
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"prediction is hard, especially about the future"
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