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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.,更多细节参见夫子

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Crucially, this distribution of border points is agnostic of routing speed profiles. It’s based only on whether a road is passable or not. This means the same set of clusters and border points can be used for all car routing profiles (default, shortest, fuel-efficient) and all bicycle profiles (default, prefer flat terrain, etc.). Only the travel time/cost values of the shortcuts between these points change based on the profile. This is a massive factor in keeping storage down – map data only increased by about 0.5% per profile to store this HH-Routing structure!

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// 测试函数:验证排序正确性