Leeds say they will struggle to break even on Vegas as the Super League teams have to pay all their own costs. So how difficult a decision was it to give up a home game to go? “It was a big decision and one that we didn’t take lightly. Part of our strategy is to constantly raise our profile and when you looked at the results from a marketing and audience perspective for Wigan v Warrington in Vegas last year, the eyeballs on that were incredible. You don’t get given a pot of money: you have to generate your own money through ticket sales. But like Leeds, we felt that we have a big enough fanbase to financially support our ability to go out there. It’s an incredibly tough schedule but to put ourselves on that stage was too big an opportunity to turn down. A year ago we said: ‘What if we won the Grand Final? It’ll be the World Club Challenge and straight into Vegas.’ We just decided to worry about it when it happens. And now it’s happened!”
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按照规划，科研团队将开展更长周期的小鼠空间科学实验，模拟人类在轨驻留半年以上的生活，研究小鼠的生理响应与空间适应性。
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.