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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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Krebs::OutputStream

@KbsEcho · Post #556 · 08/11/2025, 11:03 AM

今天调试时被 Keystone 创了,发现一个比较奇怪的行为: 对于汇编 mov rax, qword ptr gs:[0x58] Keystone 将编码为 65 48 A1 58 00 00 00 00 00 00 00 而 GCC 会编码为 65 48 8B 04 25 58 00 00 00 主要区别在于 displacement 编码方式不同(前者选择了 64bit,后者使用的是 32bit),其实都没有错,因为这条指令本身有歧义。但坑点在于..... 1) 如果用 Capstone 反汇编 Keystone 的编码结果,将得到 movabs rax, qword ptr gs:[0x58] 可以说是 Keystone 和 Capstone 的一个不一致的地方... (也是我说 Keystone 行为奇怪的原因) 2) Keystone 的结果长了两个字节😇 3) 无法补救,因为 Keystone 不支持 NASM 语法中指定 displacement 的编码方式 mov rax, qword ptr gs:[dword 0x58] # ERROR 目前没有想到好的解决办法,只能换个汇编器,但又懒了,干脆先 dirty patch 一下罢... 🔗相关链接 https://github.com/keystone-engine/keystone/issues/430 https://scz.617.cn/misc/201811071803.txt #Assembly

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叮噹貓iOS资源/限免/脚本分享频道

@ddm1023 · Post #916 · 12/26/2023, 09:52 AM

#脚本#QuantumultX#Loon#Surge#Shadowrocket#Stash#Crack#图像 ✅#Assembly 👤 脚本作者: @ios151 📌 脚本功能: 解锁永久会员 💳 特别说明: 一次性解锁 ⬇️ 下载地址: 点我下载 🔗 脚本链接: 点我复制 和Persona同脚本 🔄 脚本转换: 点击传送 ✈️导航💬群组🤖投稿🎁福利

Crypto M - Crypto News

@CryptoM · Post #64846 · 04/10/2026, 03:47 AM

🚀 Rongqi Technology Delivers Equipment for Meta Smart Glasses Rongqi Technology announced on an interactive platform that it has begun delivering assembly equipment for Meta's smart glasses. According to Jin10, the company's annual order volume will largely depend on the end sales of Meta's smart glasses and will be influenced by Meta's production schedule. #RongqiTechnology#Meta#SmartGlasses#Technology#EquipmentDelivery#Assembly#Jin10