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.
Раскрыты подробности похищения ребенка в Смоленске09:27,推荐阅读夫子获取更多信息
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Here there be Titans! Apple TV's MonsterVerse series Monarch: Legacy of Monsters returns with a vengeance for Season 2, which introduces a terrifying new beast: Titan X. An aquatic beast of immense power, Titan X has the potential to be the most destructive monster we've seen in the MonsterVerse. It's so threatening, in fact, that the trailer suggests the only way to take it out is by unleashing both Godzilla and King Kong against it. You know what they say: Let them fight.* — B.E.