Abstract: A method, system, and/or computer program product manages the lifecycle of trained models used to deliver cognitive services. One or more processors obtain and deploy a cognitive engine that utilizes artificial intelligence (AI), machine learning, and/or similar algorithms. One or more processors obtain and deploy a version of a trained model that includes data that supports cognitive operations of the cognitive engine within a cognitive service. In response to changes to the input used to produce the trained model, one or more processors obtain and deploy a subsequent version of the trained model in support of the cognitive service.

Abstract: A method, system, and/or computer program product manages the lifecycle of trained models used to deliver cognitive services. One or more processors obtain and deploy a cognitive engine that utilizes artificial intelligence (AI), machine learning, and/or similar algorithms. One or more processors obtain and deploy a version of a trained model that includes data that supports cognitive operations of the cognitive engine within a cognitive service. In response to changes to the input used to produce the trained model, one or more processors obtain and deploy a subsequent version of the trained model in support of the cognitive service.

Abstract: Data validation techniques are provided. For example, such techniques complement user entries associated with events of interest through context. In one aspect of the invention, a technique for processing one or more user entries associated with one or more events of interest includes the following steps/operations. Context associated with the one or more events of interest is obtained. At least a portion of the obtained context is associated with one or more user entries representing events of interest. At least a portion of the one or more user entries is evaluated, responsive to at least a portion of the context. An indication of the one or more events of interest is provided, responsive to the evaluation.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.

Abstract: The invention addresses the disadvantage of automated vehicle traffic management systems by providing a solution for predicting and avoiding traffic congestion before the congestion is experienced. The invention includes a decentralized mechanism for predicting congestion. An exemplary embodiment of the invention uses a system of sensors to determine current traffic flow; the sensors communicate their state to a network of servers and then an algorithm is applied to the collected data to predict traffic congestion; upon detection of congestion, signals are communicated to the system controllers to prevent the traffic congestion.