本地 vs 自托管 vs 离线：为敏感数据选择正确的 AI 部署
本地、自托管和离线经常被互换使用——但它们含义不同且提供不同的合规保证。以下是如何为敏感 AI 数据工作负载选择正确的部署模型。
"本地「、」自托管「和」离线"这三个术语经常被互换使用——但它们的含义不同，提供不同的合规保证。理解这些区别对于在敏感数据环境中正确部署 AI 至关重要。
自托管意味着你运行软件，但可能在云基础设施上（AWS、Azure、GCP）。数据仍在第三方数据中心。
本地意味着软件在你控制的硬件上运行，在你的网络边界内。但可能仍有出站连接用于许可、更新或遥测。
离线意味着完全没有网络连接。没有入站，没有出站。这是最高级别的数据隔离，用于机密数据和最敏感的工作负载。
选择哪种模型取决于你的数据敏感度、监管要求和运营能力。
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