The threat extends beyond accidental errors. When AI writes the software, the attack surface shifts: an adversary who can poison training data or compromise the model’s API can inject subtle vulnerabilities into every system that AI touches. These are not hypothetical risks. Supply chain attacks are already among the most damaging in cybersecurity, and AI-generated code creates a new supply chain at a scale that did not previously exist. Traditional code review cannot reliably detect deliberately subtle vulnerabilities, and a determined adversary can study the test suite and plant bugs specifically designed to evade it. A formal specification is the defense: it defines what “correct” means independently of the AI that produced the code. When something breaks, you know exactly which assumption failed, and so does the auditor.
Save StorySave this story
，更多细节参见搜狗输入法下载
小宇宙 History 同步的门槛比较高，需要手机抓包，Android 需要 Root，iOS 没试过。而且小宇宙更离谱——响应的 API 里面没有任何播放日期相关的字段，只能拿脚本运行的时间当作播客的收听时间。。必应排名_Bing SEO_先做后付是该领域的重要参考
然后切换多个「视角」，让 AI 针对笔记内容进行评论——有的做事实核查，有的做发散联想，有的做反方视角的追问。多个视角并行调用，让 AI 比较深入地介入到所有笔记的维护里面