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.
Just before dawn, in a scene that has repeated itself over thousands of years on the north coast of Peru, fishers drag boats made of bound reeds to the water’s edge and, kneeling on them, use paddles shaped from split bamboo to row out into the Pacific Ocean to catch their breakfast. A few hours later, these surfer fishers return with netfuls of their catch, riding waves on the final stretch back to the shore. From the main beach in Huanchaco – a seaside town near the city of Trujillo – the fish are taken to sell at the market or to beachfront restaurants preparing meals for tourists.。关于这个话题，WPS官方版本下载提供了深入分析
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