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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In a recent blog post, Google announced that Gemini can now access your Google Workspace Chat history. If you've ever spent time scrolling through several days, or even weeks, of conversation to find information, you can appreciate how useful this could be.