The finding, from a recently published research paper, is based on results of experiments correlating specific individuals with accounts or posts across more than one social media platform. The success rate was far greater than existing classical deanonymization work that relied on humans assembling structured data sets suitable for algorithmic matching or manual work by skilled investigators. Recall—that is, how many users were successfully deanonymized—was as high as 68 percent. Precision—meaning the rate of guesses that correctly identify the user—was up to 90 percent.
苹果的隐私设计哲学贯穿始终：python-apple-fm-sdk 调用的基础模型完全在本地运行，数据不离开设备。苹果整套 AI 体系在必须上云的场景里，走的是 Private Cloud Compute，数据处理完即删除，苹果无法访问。
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