More than 50 years since the last Apollo mission, Nasa is preparing to send astronauts back to the Moon.
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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新时代以来，无论是打赢脱贫攻坚战，全面建成小康社会，还是攻克一个个“卡脖子”关键核心技术，加快推进高水平科技自立自强，无论是让天更蓝、水更清、空气更清新，还是刹住了一些长期没有刹住的歪风，纠治了一些多年未除的顽瘴痼疾，桩桩件件都是实实在在干出来的。
第一方面，除了短任务链条的数据分析、生成、检索等方面的应用，智能体现在规模化应用场景大体可以概括为两类，一是在编程领域，编程是智能体最理想的"练兵场"，环境隔离、容错率高，目标明确、目前规划能力能应对，程序可执行，还有即时的执行反馈。这令其成为智能体第一个大规模、商业化的突破口。二是在各行各业的各种业务（销售、客服、人力等）的专用智能体可以集合成一个大类，有一个共同点：目前主要是工作流自动化类型，其实这也是应对智能体深度理解（规划、决策）能力不足的权宜之计，通过把智能体的任务的开放性降低、给出参考工作流程、定义可用的有限工具集等来提高智能体在这些任务上的工作质量。智能体进一步的规模化应用需要其能力进化，为企业能够带来切实的价值。，更多细节参见服务器推荐