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Source channel @githubtrending · Post #15239 · Oct 21

#python#artificial_intelligence#cloud_ml#computer_systems#courseware#deep_learning#edge_machine_learning#embedded_ml#machine_learning#machine_learning_systems#mobile_ml#textbook#tinyml You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering. https://github.com/harvard-edge/cs249r_book

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AIGC

@aigcrubbish · Post #158 · 01/27/2026, 05:06 PM

[$] Implicit arguments for BPF kfuncs Linux 内核的 kfunc 机制允许 BPF 程序直接调用内核函数。目前内核中有超过 300 个 kfunc,功能涵盖字符串处理(如 `bpf_strnlen()`)到自定义调度器(如 `scx_bpf_kick_cpu()`)等。 有时,这些 kfunc 需要访问 BPF 程序无法直接获取的上下文信息,因此无法通过参数传递。Ihor Solodrai 提交的“隐式参数”补丁集旨在解决这个问题,它允许 kfunc 隐式地接收额外的上下文参数。 原文链接:https://lwn.net/Articles/1055559/ #Linux#内核#BPF#kfunc #AIGC Read more