As an Amazon MGM Studios theatrical release, Amazon is giving Prime members access to an exclusive early screening of Project Hail Mary on March 16, 2026 at 7 p.m. local time in select theaters across the country. Tickets are now available through Fandango on a first-come, first-serve basis. Navigate to the Project Hail Mary landing page on Amazon.com and click on "buy tickets" in the bottom corner. You'll then be prompted to sign into your Amazon Prime account and redirected to Fandango to select your tickets. All early access showings will be on premium large format screens, including IMAX, Dolby Cinema, 4DX, and 70mm, so you can watch astronaut Ryland Grace's interstellar adventure in the most immersive way possible.
这几天，王守芬老人一直盼着响起熟悉的敲门声。王守芬自幼患有小儿麻痹症，几十年来一直独自生活。自从去年重阳节前夕王守芬在家中不慎摔伤后，马怀龙常常拎着新鲜菜肉上门，帮她做饭、打扫卫生，带她换药复查。王守芬感受到了马怀龙的真诚，主动把钥匙交给了他。
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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.