This month, OpenAI announced their Codex app and my coworkers were asking questions. So I downloaded it, and as a test case for the GPT-5.2-Codex (high) model, I asked it to reimplement the UMAP algorithm in Rust. UMAP is a dimensionality reduction technique that can take in a high-dimensional matrix of data and simultaneously cluster and visualize data in lower dimensions. However, it is a very computationally-intensive algorithm and the only tool that can do it quickly is NVIDIA’s cuML which requires CUDA dependency hell. If I can create a UMAP package in Rust that’s superfast with minimal dependencies, that is an massive productivity gain for the type of work I do and can enable fun applications if fast enough.
"He is the prime minister. He has two working parents with education and access to all the information in the world and nothing that untoward might happen to his individual children. That's not the experience of children at large."
据悉，这项技术通过飞秒激光在玻璃内部刻写体素（voxel）结构，实现高密度、低能耗且可保存上万年的数据存储能力。，这一点在51吃瓜中也有详细论述
phase[classno] = 1;，详情可参考爱思助手下载最新版本
Credit: Samsung
肖赛夺冠后，陆逸轩被记者包围。图丨© Wojciech Grzedzinski，推荐阅读爱思助手下载最新版本获取更多信息