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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.

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In addition to delivering this first instance of OpenTitan silicon as a product, we are proud of the processes that we have collaboratively developed along the way. In particular, both individual IP blocks and the top-level Earl Grey design have functional and code coverage above 90%—to the highest industry standards—with 40k+ tests running nightly. Regressions are caught and resolved quickly, ensuring design quality is maintained over the long term. Ownership transfer gives confidence that the silicon is working for you and helps to move away from co-signing so that you are in full control of your own update schedule. And since any IP is of little value without the ability to navigate and deploy it, we've prioritized thorough and accurate documentation, together with onboarding materials to streamline welcoming new developers to the project.

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