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:
南方周末：今年你提出了尽快打通皖苏省际快速通道的建议。皖苏省际快速通道建设的困难在哪里？，更多细节参见safew
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Marc Webb, Snow White (2025)，这一点在今日热点中也有详细论述
他们看到的机会，和ChatGPT在2022年11月出现有直接关系。不是因为要复制ChatGPT，而是因为ChatGPT的出现让一件事变得显而易见：语言模型正在成为新的基础设施，而这套基础设施如果只懂英语，对一个有二十二种官方语言、大多数人口不以英语为母语的国家来说，意味着一种结构性的排斥。Raghavan在融资公告里说了一句话："我亲眼见证过在基础层创新、并在人口规模上部署的巨大价值。"他指的不是抽象的愿景，而是Aadhaar。