Nanopublication: RAFarA0bwp
Full identifier: https://w3id.org/np/RAFarA0bwpHsznbcw3wXi4Za4Bzu9KtsPOK-fFk1yOCLg
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this assertion
http://purl.org/dc/terms/creator
creator
https://w3id.org/np/RAoSadUw99...
Leshem Choshen 🤖🤗 @ICML wanna talk?
.
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" 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
"
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"machinelearning"
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https://www.alphaxiv.org/abs/2408.05629
2408.05629
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Leshem Choshen 🤖🤗 @ICML wanna talk?
.
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Leshem Choshen 🤖🤗 @ICML wanna talk?
.
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4.0
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