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:
Fermaw cannot realistically slow down the stream more than that since it would stutter real traffic that has a download-y pattern. There is a possibility that he could enforce IP bans on patterns that display it but it would have to risk blanket bans against possible CGNAT traffic. There are ways to get around it but it prolongs the inevitable.
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