Clearly, if not breaking developers and users was a priority, we would not have been where we are today, or would we? Even ignoring bugs and design changes, in which way does it serve users to phase out Rosetta 2, which in a container-heavy world is more or less required for developers due to the ecosystem of ARM64 Linux containers being nowhere near as widespread as for AMD x86-64 ones, and which keeps many applications runnable that otherwise wouldn't be?
然而，品牌的长远增长，从来都不止于“领导更替”或“节日短期策略”的调整。对整个零食行业而言，春节的流量红利终究是一时的，真正的增长源泉，永远来自对消费者需求的持续洞察与精准回应。
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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.