Bank of America had 80 patents in artificial intelligence during Q3 2023. Bank of America Corp filed several patents during Q3 2023. One patent describes a system that predicts anomalies in a computing environment, identifies the system configuration needed to run a workload, searches for a suitable cloud instance, and switches the workload to the identified instance. Another patent relates to message processing, where an application message is routed to a message storage system if its priority score does not exceed a threshold, and is routed to a message bus if there is sufficient processing capacity. Another patent involves evaluating and loading data feeds based on artificial intelligence input, including analyzing metadata to determine the likelihood of a feed failing to load and correcting errors if necessary. Another patent describes a system that detects anomalies in a computing environment based on a comparison between the current state vector and the normal state vector of a component, and takes pre-configured actions to correct the predicted anomaly. Lastly, a patent discusses a system that splits text into portions, extracts context information, compares the information, activates additional logic gates if necessary, updates the context information, and generates an output. GlobalData’s report on Bank of America gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Bank of America grant share with artificial intelligence as a theme is 48% in Q3 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Restoring a system by load switching to an alternative cloud instance and self healing (Patent ID: US20230273852A1)

The patent filed by Bank of America Corp. describes a system for managing anomalies in a production computing environment. The system includes a production computing environment with multiple components, a centralized data repository, multiple cloud infrastructures, and at least one processor. The processor receives data feeds related to the components, predicts anomalies based on the data feeds, identifies the system configuration needed to run the current workload, searches the cloud infrastructures for a compatible cloud instance, initiates the identified cloud instance, and switches the workload to the cloud instance.

The system also includes a method for managing anomalies in the production computing environment. The method involves receiving data feeds for the components, generating current state vectors based on the data feeds, comparing the current state vectors with normal state vectors, predicting anomalies when deviations are detected, identifying the system configuration for the current workload, searching the cloud infrastructures for a compatible cloud instance, initiating the cloud instance, and switching the workload to the cloud instance.

The predicted anomalies can include hardware device errors or failures, logical errors in software applications, data breaches in software applications, and errors in accessing software applications. The system can search a repository for corrective actions corresponding to the predicted anomalies and take the identified corrective actions to correct the anomalies.

The system can also detect when the predicted anomalies have been corrected and switch the workload back to the original system. The processor can use quantum computing to process data. The system can identify the cloud instance with the lowest pricing by comparing the pricing associated with each detected cloud instance.

Overall, the system and method described in the patent aim to efficiently manage anomalies in a production computing environment by predicting anomalies, identifying compatible cloud instances, and switching workloads to the cloud instances.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.