В Финляндии предупредили об опасном шаге ЕС против России09:28
“我与中国的故事始于20多年前的太仓。”海瑞恩说，海瑞恩集团在太仓二十余载，从落地发展到深度融入本地产业生态，亲历了中国市场的持续开放与营商环境的不断优化。海瑞恩集团深耕精密制造领域，2004年成立的海瑞恩精密技术（太仓）有限公司，是该集团在中国设立的第一家工厂、亚洲第一家产品生产基地。
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Губернатор Курской области Александр Хинштейн опроверг информацию о большом числе жертв при ударе Вооруженных сил Украины (ВСУ) в приграничье. Свой комментарий по ситуации он разместил в Telegram-канале.
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Цены на нефть взлетели до максимума за полгода17:55。业内人士推荐Line官方版本下载作为进阶阅读
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.