We can see that the threshold map distributes perturbations more optimally than purely random noise, resulting in a clearer and more detailed final image. The algorithm itself is extremely simple and trivially parallelisable, requiring only a few operations per pixel.
For reinforcement learning training pipelines where AI-generated code is evaluated in sandboxes across potentially untrusted workers, the threat model is both the code and the worker. You need isolation in both directions, which pushes toward microVMs or gVisor with defense-in-depth layering.
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AI 手机的道路，不会只有「孤勇者」