19 分钟RAG会就此终结吗?Anthropic的新提示缓存
你可以根据真实工作负载,权衡缓存写入附加费与读取节省的成本,估算提示缓存何时划算。
LiveOverflow. 视频将提示词注入描述为一种经典的注入攻击,目标是混合指令与不可信数据的系统,并给出一个具体的内容审核示例:攻击者借此陷害无辜用户。从“模型是攻击目标”转变为“应用才是攻击目标”,正是文章开篇要求建立的思维方式。
将本视频视为概念指导。在权限、保留策略、日志记录和人工审核边界明确之前,不要使用真实公司数据。
将提示词注入建模为不可信数据混合问题,并围绕工具调用设计边界。
具备一般的Web安全直觉会有所帮助;不要求预先了解LLM安全。
最后审核:2026年5月18日
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A cloud-vendor-specific complement to the Macquarie specialization: AWS's own Generative AI Security Scoping Matrix, OWASP Top 10 for LLMs, and MITRE ATLAS, walked through governance, legal, and compliance controls for five different AI deployment scopes — from consumer apps to self-trained models. Not GDPR-specific, but a genuinely practical advanced pick for teams whose AI workloads actually run on AWS and need concrete data-governance and compliance controls, not just theory.
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少有的真正为法案适用对象编写的《人工智能法案》课程:它面向采用AI的中小企业,而不是开发AI的实验室。课程托管在欧盟委员会自有的技能平台上,将法律层面的角色、义务和风险分类,与大多数合规课程忽略的安全问题(提示词注入、数据泄露、供应商尽职调查)结合起来。对于部署AI的爱沙尼亚中小企业,这是切实可行的起点。