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Workshop: AI for Science: from Theory to Practice

Machine Learning for Blockchain

Luyao Zhang · Luyao Zhang


Blockchain, often heralded as the decentralized artificial intelligence and the foundational infrastructure of web3, promises to reshape industries by providing a secure, transparent, and decentralized way of recording transactions. However, despite its transparency and decentralization, blockchain faces limitations due to insufficient AI integration, impeding widespread adoption. This paper underscores the imperative of integrating machine learning (ML) to surmount these challenges, emphasizing blockchain's secure, decentralized foundation and its need for enhanced intelligence. The fusion of blockchain and ML is pivotal for overcoming constraints and unleashing the technology's full potential. This paper explores ML's empowering role in the infrastructure, application, and cross-chain dimensions, bolstering security, efficiency, and interoperability. This synergy addresses blockchain's limitations, broadening its applications and paving the way for its promise to be fully realized for the benefit of individuals and organizations.

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