For example, a 500km route might be broken down into ~100 such shortcuts. If each A* shortcut calculation explores 100-1000 detailed road segments, the total detailed segments visited by A* might be around 10,000-50,000. Compare this to the 1,000,000+ segments the old A* might have needed for the entire route!
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.
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// 5. 返回当日跨度(而非整个结果数组)
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