Many people reading this will call bullshit on the performance improvement metrics, and honestly, fair. I too thought the agents would stumble in hilarious ways trying, but they did not. To demonstrate that I am not bullshitting, I also decided to release a more simple Rust-with-Python-bindings project today: nndex, an in-memory vector “store” that is designed to retrieve the exact nearest neighbors as fast as possible (and has fast approximate NN too), and is now available open-sourced on GitHub. This leverages the dot product which is one of the simplest matrix ops and is therefore heavily optimized by existing libraries such as Python’s numpy…and yet after a few optimization passes, it tied numpy even though numpy leverages BLAS libraries for maximum mathematical performance. Naturally, I instructed Opus to also add support for BLAS with more optimization passes and it now is 1-5x numpy’s speed in the single-query case and much faster with batch prediction. 3 It’s so fast that even though I also added GPU support for testing, it’s mostly ineffective below 100k rows due to the GPU dispatch overhead being greater than the actual retrieval speed.
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我感到一种深深的无力。这种无力感，比被骗95万更让我窒息。作为儿子，我无数次试图说服她，用了我能想到的所有方法：技术手段、口头警告、寻求权威协助……但效果甚微。我们之间，仿佛隔着一层无形的墙。我说的，她不信；她信的，我无法理解。作为一个软件工程师，我始终无法在母亲的心里装上一套“杀毒软件”。，更多细节参见91视频