AI models are valuable assets, but they face risks from theft, bias, and lack of transparency. Laminator is for solve these problems by providing hardware-assisted verification for machine learning models. This help to make sure that models still secure, reliable, and legally compliant, especially as rules about fair and right use of AI keep increasing. . If companies can prove ownership and integrity, AI adoption will be safer and more reliable, preventing misuse and encouraging responsible deployment.
I would like to talk about Property cards. Al models often come with "property cards", like nutrition labels that show details about accuracy and data sources. But the problem is, we couldn't prove that developers fill these out themselves or not. Manual checks take too long, which makes it hard to enforce rules. Property attestation is good for solve this problem, it's technical way to confirm AI model properties using verifiable proof.This helps build trust, ensures compliance with the law, and gives regulators or users confidence that AI is fair and responsible.
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