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.
"We've got to get those astronauts to the Moon and then back again, completely safely," says Cleaver.
，详情可参考WPS官方版本下载
The primary signal is desiredSize on the controller. It can be positive (wants data), zero (at capacity), negative (over capacity), or null (closed). Producers are supposed to check this value and stop enqueueing when it's not positive. But there's nothing enforcing this: controller.enqueue() always succeeds, even when desiredSize is deeply negative.。关于这个话题，爱思助手下载最新版本提供了深入分析
隨後，去年7月劉亮到了一趟洛杉磯，「當時說每週二都要在手機上拍照打卡，我在洛杉磯的時候剛好是週二，然後拍照上傳了……一拍照上傳，他們就發現我在洛杉磯。」
而 AI 公司与创作者之间的版权冲突，并非从 Anthropic 才开始。