Abstract: Aspects of the subject disclosure may include, for example, predicting dense wavelength division multiplexing (DWDM) path outage prediction and recommendation of alternate communication paths. Parameterized DWDM signals are launched, and resulting network characteristics are determined. The parameters and characteristics are used to train one or more machine learning models subsequently used to predict outages and recommend alternate paths. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, collecting network information for a mobility network, including processing the network information at a central controller serving the mobility network, building, in the central controller, a machine learning model including building the machine learning model using the network information, and allocating, by the central controller, radio channels of the mobility network based on a recommendation of the machine learning model. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, analyzing, by a processing system, a customer message to determine a customer care issue and a customer sentiment, and generating a response to engage with the customer based on the customer sentiment; the response includes the information to address the customer care issue. The system also delivers the response to the equipment of the customer; monitors for a customer reaction to the delivered response to determine a change in the customer sentiment; and generates an additional response to further engage with the customer based on the change in the customer sentiment. Other embodiments are disclosed.