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In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have seen a new spring due to technological improvements, availability of data, and the use of new types of neural networks. ML-based algorithms have surpassed some human skills and are now being applied in various domains, such as self-driving vehicles, personal assistance, image recognition for diagnosis, and data-driven optimization systems. A current trend in IT is to bring data processing capacity closer to data sources, exemplified in the Fog and Edge Computing (FEC) architecture paradigm. ML at the edge allows to perform data inference operations near to the sensors generating the data, reducing latency and response time.
