EZKL
Develop a Rust-based tool to convert deep learning models into zk-SNARK circuits for privacy-preserving proofs of computation using ONNX exports and Halo2.User Review
AI Review
A1
Reviewed on 13 Feb 2024 02:43 PM
The Grant must be in support of, or directly advancing the ZK tools, libraries, community, or protocols.
EZKL's project description indicates that it focuses on the inference for deep learning models in a zk-snark, which implies a direct advancement of ZK tools or libraries.
The Grant should be focused on accomplishing the following for ZK: Usability - improving the user experience of zero-knowledge tools/libraries, not zero-knowledge rollups. This could also be technical education and documentation. Tooling - improving the developer experience or making it easier to develop applications utilizing zero-knowledge proofs or technology. Applications - technical implementations of zero-knowledge proofs and circuits, not simply applications built on top of zero-knowledge roll ups.
The project's provision of a library and CLI for working with zk-snarks enhances both usability and tooling for developers engaged in ZK technology.
The project must have been active in the last 3 months - social media and GitHub.
The GitHub activity, as outlined, shows numerous commits and some pull request activity for relevant repositories in the last 3 months.
The project should have demonstrated either concrete progress, or evidence of a substantive technical roadmap that clarifies how ZK technology will be used and advanced.
While there is activity indicating progress, there is not enough information provided to confirm a substantive technical roadmap.
The Grant deliverables should be open source.
The project is hosted on GitHub, a platform primarily used for hosting open source projects, suggesting that the deliverables are indeed open source.
Satisfy the Program General Eligibility Policy in addition to the requirements outlined above.
Without details on the Program General Eligibility Policy, it is not possible to definitively state whether the EZKL project satisfies all general eligibility criteria.