A good model isn't a description, it's an explanation. An accumulation of observations does not explain anything.
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You will have accumulated terabytes of data about the system, and yet you will still be infinitely far away from what you could learn from a 3-paragraph explanation written by someone who actually understands the system.
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A 100% complete and accurate recording of brain activity during an entire lifetime -- or a 100% 1:1 brain simulation -- would be like recording millions of search results for different queries. A description, not an explanation.
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And not conducive to building a new system that isn't just a faded Xerox of the original. (some people did try to build new search engines that way -- didn't really work out)
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Now, this is a pretty obvious statement and smart people have known this since the 1970s. Yet, I don't think too many people have thought through the implications down to their conclusion
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End of conversation
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One advantage of having a realistic model is that it is much easier to manipulate a model than the real thing in order to gain understanding/explanation of the system.
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