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:
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Additional reporting by Jonathan Fagg, Patrick Hughes and James Pearson
We explored standard advanced algorithms like Contraction Hierarchies (CH), known for their speed. But they presented their own set of deal-breakers for OsmAnd:
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