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.
Can these agent-benchmaxxed implementations actually beat the existing machine learning algorithm libraries, despite those libraries already being written in a low-level language such as C/C++/Fortran? Here are the results on my personal MacBook Pro comparing the CPU benchmarks of the Rust implementations of various computationally intensive ML algorithms to their respective popular implementations, where the agentic Rust results are within similarity tolerance with the battle-tested implementations and Python packages are compared against the Python bindings of the agent-coded Rust packages:
，这一点在91视频中也有详细论述
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方向遍历顺序说明下一个倒序（从右往左）先处理右侧，栈里存「右侧候选」上一个正序（从左往右）先处理左侧，栈里存「左侧候选」
16 February 2026ShareSave