sub:assertion {
sub:assertion dcterms:creator <
https://w3id.org/np/RAoSadUw99CeqDlR2400018nqTzR_38fT86OrTzk16Vts> ;
rdfs: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
""" ;
schema:keywords "machinelearning" , "privacy" , "quantum-securemultipartydeeplearning" , "quantumcomputing" , "securemultipartycomputation" ;
<
https://sense-nets.xyz/endorses> <
https://www.alphaxiv.org/abs/2408.05629> .
<
https://www.alphaxiv.org/abs/2408.05629> <
https://sense-nets.xyz/hasZoteroItemType> "webpage" .
}