November 2025
Intermediate to advanced
1060 pages
14h 20m
Chinese
Content preview from 人工智能系统性能工程 (Chinese Edition)
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在旧金山充满活力的街道上，创新如同101号公路上的自动驾驶车辆般司空见惯，我们置身于一个令人惊叹的人工智能世界。人工智能的迅猛发展正从各个层面重塑我们的日常生活。过去二十年间，我们经历了推荐引擎（2000年代）、人工智能助手（2010年代）以及完全自动驾驶汽车（2020年代）的时代。2030年代将更为精彩，人工智能正以惊人速度发展，并产生深远的社会影响。
我投身于快速发展的AI系统性能工程领域，源于对尖端硬件、高度优化软件与智能算法之间微妙平衡与协同设计的探索渴望——正是这些要素驱动着复杂系统与影响深远的应用场景。这一认知促使我深入"全栈式"AI性能工程领域。我渴望洞悉处理器、内存架构、网络互连、操作系统及软件框架等多重组件如何协同运作。这些交互的复杂性既是挑战，亦是机遇，正是它们点燃了我探索这项独特技术组合的热情。
本书凝聚了我作为实战机器学习与人工智能性能工程师多年的探索成果。它面向渴望理解人工智能系统多层次性能根基的工程师、研究者、从业者及爱好者。读者可能正在构建AI应用、优化神经网络训练策略、设计和维护可扩展推理服务器，或单纯对现代AI系统的运作机制充满好奇。本书旨在提供跨学科的理论实践桥梁，贯穿多领域洞见。
读者需具备神经网络基础知识及Python/机器学习基本技能。但即便缺乏这些基础，好奇的读者也能通过贯穿硬件、软件与算法的第一性原理，追随本书多维度的协同设计性能叙事。我承诺本书能满足各类读者的需求——并保证每位读者都能从中收获新知。
全书各章节将带您审视硬件架构的演进历程，深入解析软件优化的精妙之处，并通过真实案例揭示构建高性能与成本效益兼备的人工智能系统的模式与最佳实践。各章节内容层层递进，从基础概念到高级应用全面覆盖。
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.