公开(公告)号：US20230065949A1

公开(公告)日：2023-03-02

申请号：US17460371

申请日：2021-08-30

Applicant: KYNDRYL, INC.

Inventor： RESHMA REDDY RAMIREDDY ,  CARLOS DANIEL TREJO MARTINEZ ,  Zachary A. Silverstein ,  Jennifer M. Hatfield ,  Al Chakra

IPC: G06F21/55 ,  G06F16/13 ,  G10L15/22 ,  G06T11/00

Abstract: One or more computer processors detect a physical storage device within a visual proximity to a user within an augmented reality (AR) environment. The one or more computer processors capture one or more physical identifiers of the detected physical storage device. The one or more computer processors identify an indexed filesystem associated with the physical storage device utilizing the one or more captured physical identifiers, wherein the indexed filesystem contains metadata representing file content stored on the physical storage device. The one or more computer processors calculate a filesystem risk score associated with the physical storage device utilizing the identified physical identifiers. The one or more computer processors present generated graphics representing the indexed filesystem and the calculated filesystem risk score to the user within an AR viewport.

公开(公告)号：US12093897B2

公开(公告)日：2024-09-17

申请号：US17663096

申请日：2022-05-12

Applicant: Kyndryl, Inc.

Inventor： Kelly Camus ,  Shikhar Kwatra ,  Al Chakra ,  Jun Zhu

IPC: G06Q10/10 ,  G06N20/20 ,  G06Q10/0633

CPC classification number: G06Q10/103 ,  G06N20/20 ,  G06Q10/0633

Abstract: Methods, computer program products, and systems are presented. The method, computer program products, and systems can include, for instance: receiving personal inputs regarding a first individual, the first individual previously having given informed consent, automatically generating a work profile for the first individual based on the plurality of personal inputs; based on the work profile of the first individual and a preexisting work profile of a second individual, predicting a work affinity indicator for the first individual and the second individual, the predicting including using an affinity model trained via ensemble learning; and providing the work affinity indicator to a user for optional consideration in making a work-related or employment-related decision.