September 2025
Beginner to intermediate
44 pages
25m
Chinese
Overview
本作品已使用人工智能进行翻译。欢迎您提供反馈和意见：translation-feedback@oreilly.com
今年你计划投资人工智能。你的数据是否已为AI做好准备？三分之二的企业认为尚未准备就绪。随着模型逐渐成为商品，可靠的第一方数据——且需海量数据——才是AI领域的真正竞争优势。这份基础性报告深入剖析了数据+AI可靠性的核心原则，指出可观测性而非传统测试已成为成功的基石。
在《通过可观察性确保数据+AI可靠性》中，您将探索扩展检索增强生成模型的常见挑战，并学习如何运用成熟策略克服这些难题。作者巴尔·摩西和迈克尔·塞格纳将揭示可靠性如何影响性能表现，并提供实操指南，助您更明智地调配团队时间与资源。
- 利用结构化与非结构化数据，实现AI应用价值与复杂性的指数级增长
- 掌握构建可靠系统的核心原理及其在数据与AI产品中的应用
- 加速并扩展可靠的数据与AI产品计划
- 解决大规模构建数据与AI产品时常见的可靠性难题
- 优化团队时间与资源配置，实现数据与AI可靠性的最大化
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