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.
Израиль нанес удар по Ирану09:28
，这一点在快连下载安装中也有详细论述
（三）使用网络地址切换工具、批量电话卡控制工具等规避网络运营者账号注册审核规则及其他措施，大量注册网络账号的；，这一点在Line官方版本下载中也有详细论述
2024年发生的那次爱达魔都号暑期惨跌就是例证——船公司定价过高，遇冷后不干预，代理商被迫亏本40%“放血”，市场陷入混战。
Карина Черных (Редактор отдела «Ценности»)