往近看，前不久“车厘子自由”成为热议话题。受益于我国与智利等主产国的自贸协定，进口关税大幅减免，叠加跨境冷链物流效率持续提升，本产季车厘子价格显著降低。往远看，一些国家价格昂贵的西瓜，在我国早已成为便宜好吃的大众水果。今天，还有许多像吴明珠院士一样的农业科技工作者，正在向着新品种、新技术发起攻关。有市场、有政策、有技术，消费者有理由期待，更多高价水果的价格终将落在大众可接受的范围内。
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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以携程为例，2025年，其投入29亿元用于服务保障，包括重大灾害保障金、全球SOS平台（覆盖27家医疗援助机构、100万家医疗机构）以及7x24小时多语言客服。
There's also Stream.broadcast() for push-based multi-consumer scenarios. Both require you to think about what happens when consumers run at different speeds, because that's a real concern that shouldn't be hidden.