a similar idea is in complexity theory (runtime of an algorithm vs its description size), but doesn't deal in incentives
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Replying to @allgebrah
how do you figure out, at a glance, whether to optimize or to bruteforce - is there an optimal way to do this?
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Replying to @allgebrah
nah, still too obvious a question, probably answered in some paper about impl-ing Prolog; meta: quicker to figure out or to find the paper?
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Replying to @allgebrah
had similar thoughts when alpha go won. I think practically brute force & understanding are not distinct activities.
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Replying to @BagelDaughter @allgebrah
if you're wondering whether you're spending too much time trying to understand without just doing it, answer is yes
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Replying to @BagelDaughter @allgebrah
fortunately we can mostly "brute force" or use current best strategy, and v infrequently assess for inefficiency
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Replying to @BagelDaughter @allgebrah
it adds up to roughly exponential time
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Replying to @BagelDaughter @allgebrah
oops I mean exponential improvement. Cool thing about being a person is that we learn just by doing. Immersion is how we optimize
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Replying to @BagelDaughter
how would you quantify improvement so that it could be exponential?
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Replying to @allgebrah
generally that the resources of import can be consumed exponentially less over time. Moore's law style
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to put my stance better into terms of your question- "at a glance" should be indistinguishable from "after you've tried it a bit"
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