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- assertion comment " You can not run a closed model yourself, right? well... They prevent information leakage through quantum light properties What?! Simply:you can compute the network outputs but not recreate the weights and the API cannot access your data! @RLEatMIT @KfirSulimany @Dirk_Englund https://twitter.com/LChoshen/status/1823374595334009145/photo/1 The basic Idea is that for every multiplication in the network you multiply two symmetric things an input and an output matrix. So, if each side can send a matrix but only read the output each can keep their secret (one the input one the model weights) https://www.alphaxiv.org/abs/2408.05629 And apparently you can multiply (super fast) by encoding the matrix as a light wave, then the multiplication is the two waves meeting and the output is more or less the only thing you can do. I was involved in the "more or less", e.g. to avoid reconstruction through a canonical basis as inputs you can use invariances such as sending a permuted network each time https://www.alphaxiv.org/abs/2408.05629 " assertion.
- assertion endorses 2408.05629 assertion.
- assertion keywords "machinelearning" assertion.
- assertion keywords "privacy" assertion.
- assertion keywords "quantum-securemultipartydeeplearning" assertion.
- assertion keywords "quantumcomputing" assertion.
- assertion keywords "securemultipartycomputation" assertion.
- assertion wasGeneratedBy activity provenance.
- assertion wasAttributedTo RAoSadUw99CeqDlR2400018nqTzR_38fT86OrTzk16Vts provenance.
- assertion wasAttributedTo 0000-0002-0085-6496 provenance.
- assertion creator RAoSadUw99CeqDlR2400018nqTzR_38fT86OrTzk16Vts assertion.
- assertion wasAssociatedWith LChoshen provenance.
- assertion linksTo 1823374595334009145 provenance.