anadim (@dimitrispapail)
Израиль нанес удар по Ирану09:28。关于这个话题，91视频提供了深入分析
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.，更多细节参见51吃瓜
At the core of Linux ID is a set of cryptographic "proofs of personhood" built on modern digital identity standards rather than traditional PGP key signing. Instead of a single monolithic web of trust, the system issues and exchanges personhood credentials and verifiable credentials that assert things like "this person is a real individual," "this person is employed by company X," or "this Linux maintainer has met this person and recognized them as a kernel maintainer."。雷电模拟器官方版本下载是该领域的重要参考