service="${SECRETS[$var]}"
American Classic is a new series about a big Broadway star with an equally big ego who returns to his small hometown after being dealt some harsh blows. Kevin Kline stars as Richard Bean, whose Broadway run is derailed not only by a very bad review from a cutting critic but also the death of his estranged mother. Once back, he reconnects with his friends and family, and finds fresh purpose in giving back to the community — and the community theater — that made him.
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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.
比爾·蓋茨據報承認與兩俄羅斯女性有染並道歉 梅琳達稱想起「令人痛苦的時光」