习近平同志在地方工作时的两个故事，至今仍给人以深刻启迪——
So here Canva takes place, with Canva you can do all that with drag-and-drop feature. It’s also easier to use and free. Also an even-more-affordable paid version is available for $12.95 per month.，推荐阅读safew官方下载获取更多信息
gitgres is a neat hack right now, but if open source hosting keeps moving toward federation and decentralization, with ForgeFed, Forgejo’s federation work, and more people running small instances for their communities, the operational simplicity of a single-Postgres deployment matters more than raw storage efficiency. Getting from a handful of large forges to a lot of small ones probably depends on a forge you can stand up with docker compose up and back up with pg_dump, and that’s a lot easier when there’s no filesystem of bare repos to manage alongside the database.。业内人士推荐同城约会作为进阶阅读
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.，更多细节参见爱思助手下载最新版本