I think it's reasonable to say that, all else equal, more intelligent systems will be better at self-improvement. Problem is, 1) all else is not equal, and 2) even if it were, the *rate* of self-improvement is what the FOOM claim is really all about. 2/
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I don't disagree. But isn't simplifying often a route to generality?
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Yes, but its efficacy on hard problems is evidence for foom, since generalization via simplification is the route most likely to produce sudden omni-domain increases in capability.
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Chris, that isn't actually true. If an algorithm is written with optimal efficiency (leaving aside precisely what that means), then there's a sense in which the total "power" of that algorithm is determined by the # of bits in the algorithm.
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You get a "Heisenberg-like" tradeoff, where as you generalize, you say less about more, and when you specialize you say more about less, but regardless, your total information is bounded above.
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The fact that AlphaZero was (in some sense) less complex and more effective than AlphaGoZero shows that the former "structurally" improved on the latter, analogous to removing deadweight. But of course, doing that can only take you so far.
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The question is whether it's also far enough to produce sudden, superhuman performance in other domains. It would be useful if skeptics would start anchoring their perspective with predictions: where would you need to see progress before taking imminent arrival of AGI seriously?
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Example of anchoring: Books published as recently as this year discounted the general intelligence of chess AI because it did not "prune" possibilities like a human player. AlphaZero now exhibits exactly that behaviour.
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You should read through the earlier linked facebook discussion on EY's post from a few months back which discusses most of these points; https://www.facebook.com/yudkowsky/posts/10155848910529228?comment_id=10155848934404228 …
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EY, yes, but it's clearly not indefinitely practical to improve performance by reducing complexity. When something is badly built, performance can be improved by removing obstructions. Past that, increased performance requires increased complexity (e.g. human vs mouse brains).
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