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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This is what most people mean when they ask “When is Wasm going to get DOM support?” It’s already possible to access any Web API with WebAssembly, but it requires JavaScript glue code.。一键获取谷歌浏览器下载对此有专业解读
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WebAssembly with no kernel at allWebAssembly takes a fundamentally different approach. Instead of running native code and filtering its kernel access, WASM runs code in a memory-safe virtual machine that has no syscall interface at all. All interaction with the host happens through explicitly imported host functions.