✨ Today we continue our series on @Lagrange Official and their zkML technology, focusing on a key tool — DeepProve.
This solution allows for the verification of complex ML models without disclosing the data itself or the internal logic of the model. Imagine being able to prove that your model's prediction is correct without revealing either its code or the training dataset.
🔍 This is particularly important for fields where data is a commercial secret or contains sensitive information — for example, fintech, medicine, or government systems.
Using DeepProve provides a balance between the transparency of results and the preservation of confidentiality — and it is this feature that opens the door to large-scale implementation of zkML in business.
Tomorrow we will look at how Lagrange solves the scalability problem of zkML, as the speed of model verification is the key to their real use in Web3 and beyond.
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