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.
Earlier this year, Horvath testified before the U.S. Senate Committee on Commerce, Science, and Transportation, arguing the technology’s impact on more than just test scores, but on the cognitive capabilities they are intended to measure. He said that for the first time in modern history, today’s generation has failed to outperform their parents on standardized assessments. In other words, Gen Z is the first generation to be less cognitively capable than their predecessors.
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