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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.
He taught himself to use digital tools, such as Photoshop, to design clothes he would want to wear and shared the ideas on TikTok.。91视频对此有专业解读
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Why scientists fear Emperor penguins' annual moult may be killing them
Rumors also suggest the upcoming MacBook might use the A18 Pro from the iPhone 16 Pro, a chip that benchmarks faster than the M1. Even if it only has six cores, making it slower for heavy workloads than the M2, an A18 Pro-powered MacBook would still be more than enough power for basic productivity work. Not everyone needs the surprising amount of GPU power in the MacBook Air — especially if downgrading means they can save $200 to $300.，更多细节参见heLLoword翻译官方下载