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.
British YouTuber James Bruton wanted to build a giant walking robot from Star Wars – and ride around on it on his friend's tennis court. "My goal is to have something people would click on," he says.，推荐阅读快连下载安装获取更多信息
。关于这个话题，Line官方版本下载提供了深入分析
const currentTime = posToTime.get(currentPos);，推荐阅读Safew下载获取更多信息
FT Videos & Podcasts
15:40, 27 февраля 2026Россия