Dr. Emmanuel Soriano Flores, researcher at the Universidad Europea del Atlántico (European University of the Atlantic, UNEATLANTICO), analyzes the potential of the combination of two cutting-edge technologies: blockchain and machine learning (ML) together with other researchers.
Blockchain and machine learning are two cutting-edge technologies that have attracted increasing interest from researchers and academics. This is due to its potential to reshape industries and address complex challenges. As the demand for decentralized and intelligent systems grows, it is essential to understand the intersections between these two technologies.
Blockchain is a distributed ledger that enables secure and transparent transactions that do not require a fully trusted third party. The blockchain acts as a decentralized database where all transactions are recorded chronologically and immutably. In addition, each blockchain has a cryptographic hash of the previous block, which ensures the integrity of the ledger and prevents unauthorized modification or tampering. Blockchain has the potential to revolutionize business models, financial transactions, and management processes in different industries in the near future.
On the other hand, ML is a subfield of AI and is concerned with the development of algorithms and models that can be trained on large data sets to make predictions, determine patterns and linkages, and automate decision-making processes. It has been successfully applied in different fields such as natural language processing, image and speech recognition in recommender systems and predictive analytics.
Despite the great interest in the combination of these two technologies, there is little research that consolidates and examines the most current knowledge on the combined use of the applications. Therefore, this bibliometric review aims to fill the knowledge gap by providing an updated overview of the field.
The combination of these two technologies offers a great opportunity for the development of innovative applications and decentralized services that were previously impossible. Although the two have notable differences, they can be integrated and create a synergistic effect. The combination of blockchain and ML could be efficient in various applications such as fraud detection, supply chain management, healthcare, and decentralized finance.
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For further research, check the UNEATLANTICO repository.