Kyndryl, Inc.

Ana Maria Bezerra Maimoni

Clea Anne Zolotow

Marci Devorah Formato

John F Graham

Gavin Charles O'Reilly

Saritha Route

Pedro Soares

Jack Louis Cherkas

Robert Bradley Desaulniers

Mihai Criveti

A method includes training a recurrent neural network by monitoring data in a memory of a first server as the first server executes jobs and by determining an amount of computing resources used by the first server while executing the jobs and applying the recurrent neural network to data in the memory to predict an amount of computing resources that the first server will use when executing a first future job. The method also includes, in response to determining that execution of the first future job did not meet a performance criterion, making a change to the first server. The method further includes further training the recurrent neural network using a reinforcement learning technique, applying the recurrent neural network to determine that the change should be made to a second server, and in response, making the change to the second server before the second server executes a second future job.

Machine learning and optimization techniques for job scheduling

A method for retrieving a plurality of electronic images that includes obtaining images from a plurality of electronic storage sites. A first set of images containing a main protagonist is selected from the plurality of electronic images. An intent based image selection is performed from the first set of images. The intent based image selection includes tagging the first set of images with word tags identifying content of the images, creating a word cloud from the word tags, plotting the top word tags from the word cloud in a Venn diagram, and extracting images from the overlapping are of the Venn diagram.

Artificial intelligence driven image retrieval

A method, system and computer program product for data backup based on a workload behavior includes a first computer identifying, using machine learning tools, data associated with frequently accessed files on the first computer by a workload being processed by a second computer. The first computer processes the identified data associated with the frequently accessed files to generate a list of frequently accessed files by the workload, and compares the list of frequently accessed files to backup policy rules active on the first computer. Based on the comparison, the first computer identifies a mismatch between the list of frequently accessed files and the backup policy rules, and specifies a new backup rule to update the backup policy rules for each identified mismatch between the list of frequently accessed files and the backup policy rules.

Cognitive data backup

Growing community of inventors

Sao Paulo, Brazil

Ana Maria Bezerra Maimoni