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As someone else who works on systems like these, I agree training data is the whole problem. However you can use some techniques like homomorphic encryption and gradient pooling to collect training data from client code while remaining end-to-end encryption. It's hard, but it's not impossible.



Really? Have we had a revolution in homomorphic encryption such that it can be used for anything other than 1-million-times-slower proofs-of-concept?

I know IBM has released something lately, but given the source..

Does anyone use HE for the type of ML application you are describing?




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