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.
猎户座重返赛场，AI 再引外援
。heLLoword翻译官方下载是该领域的重要参考
英特尔CEO陈立武直言，AI相关的需求增加，已对电脑和智能手机方面的传统供应带来了压力，导致存储芯片短缺，价格持续上涨，在2028年前不会缓解。这和瑞银分析师团队的预测大致相同，其指出，在当前AI数据中心持续扩张的背景下，全球存储产业正呈现出明显的结构性分化，行业层面出现“有意义的供给缓解”最早也要到2028年前后。
绝对贫困历史性消除，为什么要设立5年过渡期？
Израиль нанес удар по Ирану09:28