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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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首先是大模型的持续进步，主要体现在推理模型的出现提供了更强的任务理解、规划能力，以及多模态模型的发展为智能体能够处理和生成更复杂的信息提供了基础。
ATMs in the US, and IBM would sell them overseas, where IBM had generally been