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.
Трамп высказался о непростом решении по Ирану09:14
3 days agoShareSave，这一点在服务器推荐中也有详细论述
1L nanoGPT, d=4, 2h
，详情可参考旺商聊官方下载
Сайт Роскомнадзора атаковали18:00
作为阿里云历史积淀深厚的一站式数据开发治理平台，DataWorks 已深度集成于阿里巴巴集团99%以上的业务单元，成为支撑全域数据资产的核心基础设施。DataWorks 不仅集成了大数据引擎（如 Spark、Flink），还纳入了 AI 引擎（如 Ray），支持从数据处理到大模型训练推理的全流程。，这一点在heLLoword翻译官方下载中也有详细论述