18版 - 谋好长远 干好当下(每周经济评论)

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Юра Борисов покорил всех манерами, дочь Деппа — прозрачным платьем, а Адам Сэндлер пришел в худи.Чем еще удивил «Оскар»?3 марта 2025

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It all began last December when WBD agreed to sell its Warner Bros. studio and HBO Max streaming service to the streaming giant Netflix. Days later, Paramount Skydance lobbed in a hostile bid to buy all of WBD. Amid multiple twists and turns—and the CEOs of both bidding companies separately visiting President Trump to make their cases—WBD declared on Feb. 26 that it would agree to Paramount’s bid, which had gone through various permutations to make it more appealing. Netflix co-CEO Ted Sarandos declined to sweeten the offer, saying that for Netflix the deal had always been nice-to-have, not need-to-have.

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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.

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