Lagrange provides AI with verifiable receipts, how DeepProve makes AI more trustworthy @Lagrange Official
AI models are increasingly involved in decision-making, but we often cannot verify whether the results are derived from the model as designed, which is concerning. Lagrange's DeepProve zkML technology precisely addresses this pain point.
It can generate zero-knowledge proofs for AI inference results, ensuring that the model's privacy is not compromised while proving that for some input X, the AI model indeed produced Y, which is the receipt behind trustworthiness. $LA
Technically, DeepProve claims that its proof generation speed is nearly a hundred times faster than traditional low-code methods, with faster verification and initialization setups, making it a truly practical zkML.
With this system, developers can allow users to confirm that the results are computed by the model for a certain input without disclosing model details, ensuring both security and increased trust.
Are ordinary users or companies worried about AI results being incorrect but don't know where the error lies? With DeepProve, it's like adding an anti-counterfeiting seal to AI results, making it possible to verify authenticity at any time.
This approach is particularly suitable for rigorous scenarios such as finance, healthcare, and auditing, making AI outputs truly verifiable and reliable.
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