This algorithm attempts to minimise numerically. Because of this, the quality of the dither produced by Knoll’s algorithm is much higher than any other of the N-candidate methods we have covered so far. It is also the slowest however, as it requires a greater per-pixel to be really effective. More details are given in Knoll’s now expired patent[3]. I have put together a GPU implementation of Knoll’s algorithm on Shadertoy here.
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The new partnership with NVIDIA evolves the long-standing collaboration between the two companies. OpenAI has pledged to consume 2 gigawatts of training capacity on NVIDIA's Vera Rubin systems and an additional 3 gigawatts of computing resources, likely in the form of GPUs, to run specific AI inference tasks. In other words, NVIDIA is spending a lot of money on OpenAI and then OpenAI will turn around and spend a lot of money with NVIDIA. The ouroboros must feed.
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