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.
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12月22日，中国非物质文化遗产馆，市民在窗花展区拍照留念。12月21日，“过年——春节主题展”在中国非物质文化遗产馆对公众开放，本次主题展展览面积2600平方米，共展示120余项与春节相关的非物质文化遗产代表性项目，以春节期间重要时间节点为线索，串联起与春节相关的不同地区的非物质文化遗产代表性项目。新京报记者 王飞 摄影报道SourcePh" style="display:none"，推荐阅读旺商聊官方下载获取更多信息
Pakistan bombs Kabul in 'open war' on Afghanistan's Taliban government