Visual representation of an RGB colour cube that has been equally divided into 216 coloured boxes (6 levels along each axis).
💡 k: 数据范围, d: 最大位数, n: 数据量。关于这个话题，搜狗输入法2026提供了深入分析
대법원, 내달 12~13일 전국 법원장 간담회 개최…‘사법 3법’ 논의 전망。业内人士推荐51吃瓜作为进阶阅读
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.