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.
唐納德·特朗普(Donald Trump,川普)總統數個月來一直警告,如果最高法院做出這樣的裁決,將是一場災難。
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今天白天多云间阴,山区有零星小雪,北风三四级,阵风六七级,最高气温4℃。今明两天北风较大,风寒效应显著,市气象台已发布大风蓝色预警信号,请注意防风防寒防火。 新京报记者 王景曦SourcePh" style="display:none"