(untitled) (International Journal of Innovative Research in Computer Science & Technology, 2021)
Developments in (AI) or (DLT) are now provoking lively debate in practice and academia. AI uses data to achieve goals that were previously believed to be only possible for humans. In an unsettled context, distributed ledger technology has the potential to establish consensus about information among a group of contributors. Both technologies that are needed in similar and common systems are investigated in this study. As a result, the safe pattern (DLT) or the creation of a federated learning system spread over many nodes. It has the ability to lead technological convergence, which has previously covered the technique for the major revolution in technology (IT). Earlier work summarizes many possible benefits of the convergence of DLT and AI, but only provides a limited theoretical framework to describe future real-world DLT and AI merger instances. The primary goal of this research is to disseminate by maintaining systematic previous works and offering conscientious derivative future research opportunities. This study contributes to overcoming existing constraints in AI and DLT convergence for both technologies.