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#124 Sina Kian: Reshaping Privacy in the AI & Machine Learning Revolution

Eye On A.I.

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How Homomorphic Encryption Differs From Federated Learning

Zero knowledge proof is an application of cryptography that allows a user to prove something about a set of facts without actually sharing that underlying set of facts. In a machine learning training scenario, how does this work? I mean, federated learning, you're sending the model out to different data pools that various owners have and then coming back and updating the model so that that data never has to leave the possession of the owner. So in that context, you can actually look at the health traits you care about and get proofs about the age of the person without actually knowing anything else about the person.

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