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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各营收区间的研发强度则呈“金字塔”式负相关，即研发强度的最高值和中位数都随着营收规模的增长而递减。金字塔尖是那些营收万亿元级的巨无霸企业，它们的研发强度最高值和中位数分别仅为3.27%和2.08%；而金字塔底则是营收十万元级及以下的初创小公司，它们的研发强度中位数竟高达37446.12%，最高值甚至突破47441%。