Blockchain technology has emerged as a transformative force across various industries, providing decentralized, secure, and transparent solutions. In parallel, artificial intelligence (AI) and machine learning (ML) continue to drive innovation, enabling intelligent decision-making and automation. This paper explores the integration of blockchain with AI and ML, highlighting its potential to enhance data security, trust, and efficiency in machine learning workflows. We discuss key applications, including decentralized AI marketplaces, secure data sharing, and federated learning, where blockchain ensures integrity and traceability. Additionally, we examine the challenges and limitations of this integration, such as scalability, computational overhead, and privacy concerns. Finally, we propose potential future directions for research and development in blockchain-powered AI and ML. This study aims to provide insights into the synergy between these two transformative technologies and their impact on various domains. Nonetheless, AI and ML systems encounter several challenges, including concerns over data privacy, centralized control, a lack of transparency, and susceptibility to adversarial attacks. Research aimed at ensuring data integrity and security while enabling decentralized intelligence has become increasingly crucial.
Volume 17 | Issue 1
Pages: 279-286