Abstract: Methods, apparatus, and processor-readable storage media for predicting statistics gathering times for database activity data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining activity data pertaining to at least one storage object of a given database; determining one or more times to gather statistics related to activity data pertaining to the at least one storage object of the given database by processing at least a portion of the obtained activity data using one or more machine learning techniques; and performing at least one automated action related to statistics gathering based at least in part on the one or more determined times.

Abstract: Methods, apparatus, and processor-readable storage media for predicting statistics gathering times for database activity data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining activity data pertaining to at least one storage object of a given database; determining one or more times to gather statistics related to activity data pertaining to the at least one storage object of the given database by processing at least a portion of the obtained activity data using one or more machine learning techniques; and performing at least one automated action related to statistics gathering based at least in part on the one or more determined times.

Abstract: Methods, apparatus, and processor-readable storage media for device manufacturing cycle time reduction using machine learning techniques are provided herein. An example computer-implemented method includes obtaining video input related to one or more manufacturing resources in a manufacturing environment; determining availability status information for at least one of the one or more manufacturing resources by applying one or more machine learning models to the obtained video input; and outputting the determined availability status information to at least one user device associated with the manufacturing environment.

Abstract: Methods, apparatus, and processor-readable storage media for augmenting end-to-end transaction visibility using artificial intelligence are provided herein. An example computer-implemented method includes obtaining data related to multiple transaction flows across multiple data sources within an enterprise system, and forecasting anomalies in connection with at least one of the transaction flows by applying one or more of a first set of artificial intelligence techniques to portions of the obtained data, wherein applying the artificial intelligence techniques is based on which of the multiple data sources correspond to the portions of the obtained data. Such a method further includes determining automated actions to be performed in connection with the forecasted anomalies by applying one or more of a second set of artificial intelligence techniques to portions of the obtained data related to the forecasted anomalies, and performing the automated actions in connection with the at least one transaction flow.

Abstract: Methods, apparatus, and processor-readable storage media for device manufacturing cycle time reduction using machine learning techniques are provided herein. An example computer-implemented method includes obtaining video input related to one or more manufacturing resources in a manufacturing environment; determining availability status information for at least one of the one or more manufacturing resources by applying one or more machine learning models to the obtained video input; and outputting the determined availability status information to at least one user device associated with the manufacturing environment.

Abstract: Methods, apparatus, and processor-readable storage media for transaction visibility framework implemented using artificial intelligence are provided herein.