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很多有灵气的作者，就困在这第一步。我身边有一位优秀的青年写作者，名校、专业好，读书多、很有想法，我常常被他新颖的见解所吸引。他很爱说的一句话是：等我写出来，肯定会有很多人与您一样的感受。我不断鼓励他，却总是听到他回复：开了头，但总是不完美。总想一步到位，结果呢？笔尖生了锈，灵感发了霉。
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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.。WPS官方版本下载是该领域的重要参考