The official added that the Pentagon would simultaneously label Anthropic as a supply chain risk.
2026年的涨价潮，表面是存储周期，实则是AI算力革命对传统消费电子产业的第一次“成本清算”。当所有终端都想跑大模型时，硬件的物理瓶颈和成本瓶颈暴露无遗。手机行业过去十年“性能翻倍、价格不变”的黄金时代，或许真的结束了。对于行业而言，这既是危机，也是重新定义价值、优化产品结构的契机。
。WPS官方版本下载是该领域的重要参考
Филолог заявил о массовой отмене обращения на «вы» с большой буквы09:36
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.