Bank of America Corporation

Bank of America Corportion

Shakti Suman

Jisoo Lee

James McCormack

In one or more embodiments, one or more systems, processes, and/or methods may receive first task sets that include respective first tasks and one or more of respective first priorities, respective first minimum computing resource allocations, and respective first maximum processing times; receive first satisfaction information associated with processing the first task sets; receive first execution metric information associated with processing the first task sets; determine a first pattern based at least on the first satisfaction information and based at least on the first execution metric information; receive second task sets that include respective second tasks and one or more of respective second priorities, respective second minimum computing resource allocations, and respective second maximum processing times; determine, based at least on the first pattern, computing resources allocations for the second task sets; and determine, based at least on the first pattern, a processing order for the second task sets.

System and method of training machine learning algorithm to satisfactorily allocate resources for task execution

Various features described herein may include ways of processing multiple images to determine whether any duplicates are among the multiple images. A hashing algorithm may be used to create a hash key of an image. Multiple hash keys corresponding to multiple images may be compared to determine whether those images are duplicate images. A root mean square algorithm may be used to further identify whether multiple images are duplicate images. An image variation engine, which uses intensity coding, may be used to display differences between images. For example, similar areas in images may be drawn with low intensity or high opacity, while different areas in images may be drawn with high intensity or low opacity.

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Muzaffarpur, India

Shakti Suman