Files
website-v2/data/projects/zkml.ts
2023-09-08 19:34:02 +01:00

24 lines
1.3 KiB
TypeScript

import { ProjectInterface } from "@/lib/types"
const description = `
ZKML is a solution that combines the power of zero-knowledge proofs (ZKPs) and machine learning to address the privacy concerns in traditional machine learning. It provides a platform for machine learning developers to convert their TensorFlow Keras models into ZK-compatible versions, ensuring model privacy, data privacy, and transparent verification. ZKML can be used to verify if a specific machine learning model was used to generate a particular piece of content, without revealing the input or the model used. It has potential use cases in on-chain biometric authentication, private data marketplace, proprietary ML model sharing, and AIGC NFTs.
`
export const zkml: ProjectInterface = {
id: "zkml",
projectStatus: "active",
image: "",
name: "ZKML",
tldr: "ZKML (Zero-Knowledge Machine Learning) leverages zero-knowledge proofs for privacy-preserving machine learning, enabling model and data privacy with transparent verification.",
description,
links: {
github: "https://github.com/socathie/circomlib-ml",
},
tags: {
keywords: ["Anonymity/privacy", "Scaling"],
themes: ["research"],
types: ["Proof of concept", "Infrastructure/protocol"],
builtWith: ["circom", "halo2", "nova"],
},
}