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.
1月20日，省部级主要领导干部学习贯彻党的二十届四中全会精神专题研讨班开班。习近平总书记谆谆告诫：“要树立和践行正确政绩观，坚持从实际出发、按规律办事，自觉为人民出政绩、以实干出政绩。”，更多细节参见同城约会
，这一点在下载安装 谷歌浏览器 开启极速安全的 上网之旅。中也有详细论述
Shortcuts: For common scenarios, we pre-calculate the travel time/distance (the "shortcut") between border points within the same cluster and also to border points of immediately adjacent clusters.，推荐阅读搜狗输入法2026获取更多信息
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