The same is done for your target point within its own cluster (finding paths from all its border points to your actual destination).
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Publication date: 28 February 2026
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.，详情可参考服务器推荐
2026-02-28 00:00:00:0本报记者 张 枨 薛志龙代表——
"(1) Provide an accessible interface at account setup that requires an account holder to indicate the birth date, age, or both, of the user of that device for the purpose of providing a signal regarding the user’s age bracket to applications available in a covered application store.，更多细节参见同城约会