opp/ai: Optimistic Privacy-Preserving AI on Blockchain

TL;DR

The paper introduces opp/ai, a hybrid framework combining zkML and opML to enable privacy-preserving and efficient AI services on blockchain platforms, addressing computational and privacy challenges.

Contribution

It presents a novel hybrid framework integrating zero-knowledge machine learning with optimistic machine learning for blockchain AI applications.

Findings

Framework effectively balances privacy and efficiency.

Demonstrates adaptability across various scenarios.

Enhances privacy protection in blockchain AI services.

Abstract

The convergence of Artificial Intelligence (AI) and blockchain technology is reshaping the digital world, offering decentralized, secure, and efficient AI services on blockchain platforms. Despite the promise, the high computational demands of AI on blockchain raise significant privacy and efficiency concerns. The Optimistic Privacy-Preserving AI (opp/ai) framework is introduced as a pioneering solution to these issues, striking a balance between privacy protection and computational efficiency. The framework integrates Zero-Knowledge Machine Learning (zkML) for privacy with Optimistic Machine Learning (opML) for efficiency, creating a hybrid model tailored for blockchain AI services. This study presents the opp/ai framework, delves into the privacy features of zkML, and assesses the framework's performance and adaptability across different scenarios.