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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.
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第十二条 已满十四周岁不满十八周岁的人违反治安管理的，从轻或者减轻处罚；不满十四周岁的人违反治安管理的，不予处罚，但是应当责令其监护人严加管教。
第二十六条 行政执法监督机构对行政执法监督中发现的问题，根据不同情形制发行政执法监督督办函、行政执法监督意见书或者报请本级人民政府制发行政执法监督决定书等督促有关行政执法机关予以纠正。