physics is not a game with rules, it is about discovering the rules of the game.
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Consider the Atari player that preceeded Alpha Go: it was not given the rules of Donkey Kong either. We are always approximating a function to optimize some loss criterion; it does not matter if the loss represents game score, prediction accuracy or model size etc
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Not me. I think I have just given up on the humans and don't want to live on this planet any more.
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That is the most scary thing an AI researcher can say.
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As a person extremely well familiar with both fields I can assure this is not the case. The difference lies in Go being a closed well-defined system. Physics has is open with new outside info coming in all the time.
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My intuition for understanding how the reconciliation will work starts via the AdS CFT equivalence. Ontologically there is no space, it can only be projected over how stable packets of information travel over large distances in a graph, as seen from an embedded observer
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Real intelligence >> AI and optimization/classification/reinforcement
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Mechanism is now computationalism. We can show that computation is necessary and sufficient for producing all observables. "Physical reality" is a thing that nobody has ever seen, we cannot treat it as if we could be acquainted with it.
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'We can show that computation is necessary and sufficient for producing all observables.' Go ahead and Stockholm will be glad to offer you a Prize :) Seriously now I hope you understand this is a statement of omniscience refuted by Fitch's paradox. http://www.digitalcosmology.com/Blog/2011/08/28/is-fitchs-paradox-of-knowability-just-a-scholastic-argument/ …
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