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.
#include <string.h
，推荐阅读夫子获取更多信息
The band on the stadium concourse were playing a familiar tune in the immediate aftermath of England’s latest debacle on Saturday. “Zombie! Zombie!” the vocalist sang, ostensibly in tribute to Ireland’s record 42-21 victory at Twickenham. Alternatively he might just have been riffing on the horribly listless, blank-eyed performance that ended England’s Six Nations title hopes for another year.
The U.S. women also beat Canada 2-1 in overtime, the first time the Americans swept both Olympic hockey tournaments. The celebration of the twin victories has been shadowed by U.S. politics almost since the final horn of the men’s game.
“20年一遇的创富窗口。普通人也能入局机器人。”