The traditional way to do this most naively would literally be to like represent the matrix multiply operation as a circuit. When you apply a snark to that circuit, the prover is proving not just that it knows the product, but that it computed in a specific way. So with these special purpose snarks I'm referring to, you don't even have to have the prover cryptographically commit to these product matrices. That could blow away this whole goal of having kind of a low order runtime overhead for the prover to compute the proof. This all falls under the category that people might be starting to hear about, just like CKML.
This week, Anna chats with Justin Thaler, Associate Professor at Georgetown. They cover Justin’s academic history and discuss what led him to working on interactive proofs and SNARKs. They also take a look at several other topics such as the Thaler Book Study Group, his earlier work Spartan, comparing the security of different rollups built with SNARKs and STARKs and more.
Here are some additional links for this episode:
Apply for zkSummit9 here: zkSummit9 Ticket Application.
Check out ingonyama.com to learn more about Zero Knowledge Hardware acceleration.
Aleo is a new Layer-1 blockchain that achieves the programmability of Ethereum, the privacy of Zcash, and the scalability of a rollup.
Interested in building private applications? Check out Aleo’s programming language called Leo by visiting http://developer.aleo.org.
You can also participate in Aleo’s incentivized testnet3 by downloading and running a snarkOS node. No sign-up is necessary to participate.
For questions, join their Discord at aleo.org/discord.
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