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jasonmorton

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Show HN: Turn ML/AI models into zero-knowledge proofs

github.com
4 points·by jasonmorton·3 anni fa·1 comments

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jasonmorton
·anno scorso·discuss
This lets you verify the signature on the model. It won’t help you tell that a decision came from that model. If you want to verify the inference that a model makes, check out https://github.com/zkonduit/ezkl (our project).
jasonmorton
·2 anni fa·discuss
You can ZK an XGBoost or neural net with https://github.com/zkonduit/ezkl
jasonmorton
·3 anni fa·discuss
Here is the twitter thread providing an introduction and some background: https://twitter.com/ezklxyz/status/1712940546182774936
jasonmorton
·3 anni fa·discuss
> Checking the work takes the same resources as doing the work. > As much as this would be wonderful in a universe where it's possible, it's simply not possible.

We do live in that universe, under some currently believed assumptions. An NP-complete problem is an example of something where checking a solution is (thought to be) easier than finding one.

Zero-knowledge proofs make it such that checking that a computation (such as inference) has been done correctly is easier than doing the computation (even keeping some parts private). A great reference is here: https://people.cs.georgetown.edu/jthaler/ProofsArgsAndZK.pdf
jasonmorton
·3 anni fa·discuss
One can cryptographically prove the correct inference of a small AI model now with https://github.com/zkonduit/ezkl (our open-source package).
jasonmorton
·3 anni fa·discuss
Our project proves AI model execution with cryptography, but without any trusted hardware (using zero-knowledge proofs): https://github.com/zkonduit/ezkl