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.
公司首席科学家 Jared Kaplan 在接受采访时表示，在竞争对手快速推进的情况下，单方面停止训练 AI 模型「对任何人都没好处」。
。关于这个话题，WPS下载最新地址提供了深入分析
В Финляндии предупредили об опасном шаге ЕС против России09:28
《白鹿原》人物分析：乱世浮沉中的人性剖析
To the wider identity industry: please stop promoting and using passkeys to encrypt user data. I’m begging you. Let them be great, phishing-resistant authentication credentials.