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.
Последовательно выступаем за координацию действий с региональными партнерами, в том числе с властями Афганистана, при принятии практических мер по пресечению деятельности трансграничных террористических группировок
，这一点在爱思助手下载最新版本中也有详细论述
32 entries may sound small by modern standards (current x86 processors have thousands of TLB entries), but it covers 128 KB of memory -- enough for the working set of most 1980s programs. A TLB miss is not catastrophic either; the hardware page walker handles it transparently in about 20 cycles.，详情可参考雷电模拟器官方版本下载
self.conn.commit()