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.
VFDs with full-size CRTs typical of other computer terminals, and conventional
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同时，消费者的需求也在向健康升级，少盐、少油、低脂成为主流。但目前餐饮市场中，品牌对用户的细分需求并不重视，我们并没有为用户解决更多问题。例如，针对甲亢患者的低碘餐、对糖尿病患者友好的餐食，这类细分需求市场，几乎处于空白状态。