The integration of machine learning with blockchain technology has witnessed increasing interest, driven by the vision of decentralized, secure, and transparent AI services. In this context, we introduce opML (Optimistic Machine Learning on chain), an innovative approach that empowers blockchain systems to conduct AI model inference. opML lies a interactive fraud proof protocol, reminiscent of the optimistic rollup systems. This mechanism ensures decentralized and verifiable consensus for ML services, enhancing trust and transparency. Unlike zkML (Zero-Knowledge Machine Learning), opML offers cost-efficient and highly efficient ML services, with minimal participation requirements. Remarkably, opML enables the execution of extensive language models, such as 7B-LLaMA, on standard PCs without GPUs, significantly expanding accessibility.By combining the capabilities of blockchain and AI through opML, we embark on a transformative journey toward accessible, secure, and efficient on-chain machine learning.

翻译：机器学习与区块链技术的融合，因其去中心化、安全透明的人工智能服务愿景而日益受到关注。在此背景下，我们提出opML（链上乐观机器学习）这一创新方法，使区块链系统能够执行AI模型推理。opML的核心是一种交互式欺诈证明协议，类似于乐观汇总系统。该机制为机器学习服务实现去中心化可验证共识，增强信任与透明度。与zkML（零知识机器学习）相比，opML提供低成本、高效率的机器学习服务，且参与门槛极低。值得关注的是，opML可在无GPU的标准个人电脑上运行7B-LLaMA等大型语言模型，显著提升可访问性。通过opML融合区块链与AI能力，我们开启了通往可访问、安全且高效的链上机器学习变革之旅。