Hierarchical machine learning architecture including master engine supported by distributed light-weight real-time edge engines
Abstract:
A system and method relate to a processing device implementing a master artificial intelligence (AI) engine to receive, from each of one or more real-time AI engines, a machine learning algorithm, parameters associated with the machine learning algorithm, and features employed to train the parameters, receive labeled data used to train the parameters associated with the machine learning algorithm, and construct, based on a combination rule, a master machine learning model using the features, the machine learning algorithm, and the parameters associated with the machine learning algorithm received from each of the one or more real-time AI engines.
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