SAT (short for "satisfiability") is a logic problem that given a boolean formula, it asks whether the boolean formula has an assignment that makes the problem true. An example boolean formula is:
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还有一个现象值得注意。81%的大企业目前同时在测试或使用三个以上的AI模型,比一年前高了13个百分点。没有任何一家在赢者通吃。企业的采购策略越来越像投资组合管理——不同场景配不同模型,随时可以切换,谁都不想被单一供应商锁死。
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This approach shares a lot in common with the idea of multivariate interpolation over scattered data. Multivariate interpolation attempts to estimate values at unknown points within an existing data set and is often used in fields such as geostatistics or for geophysical analysis like elevation modelling. We can think of our colour palette as the set of variables we want to interpolate from, and our input colour as the unknown we’re trying to estimate. We can borrow some ideas from multivariate interpolation to develop more effective dithering algorithms.