
Can AI be private? w/ Marks from OpenSecret
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Navigating Privacy in AI and Secure Computing
This chapter examines the pivotal role of secure enclaves and confidential computing in enhancing user privacy, particularly through the lens of OpenSecret's innovations. It highlights the challenges users face in achieving privacy while interacting with AI tools like Maple and Venice, emphasizing the necessity for accessible privacy solutions. The conversation also underscores the importance of transparency in software, advocating for open-source practices as a means to bolster trust and security in the digital landscape.
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