公开(公告)号：US20230122363A1

公开(公告)日：2023-04-20

申请号：US17505002

申请日：2021-10-19

Applicant: KYNDRYL, INC.

Inventor： Renato Lopes Ramos ,  Paulo Tomiyoshi Takeda ,  Nathan Rodrigues Levy ,  Sergio Varga

IPC: G06F9/48 ,  G06F9/50

Abstract: An application priority level of an application to be executed within a computing environment is determined. The application priority level is specific to a select entity. Using the application priority level of the application a storage resource of the computing environment to be allocated to one or more workloads of the select entity is selected. At least one workload of the one or more workloads includes the application. An action is taken, based on selecting the storage resource, to facilitate allocation of the storage resource.

公开(公告)号：US11552909B2

公开(公告)日：2023-01-10

申请号：US16920785

申请日：2020-07-06

Applicant: KYNDRYL, INC.

Inventor： Marcelo Lopes de Moraes ,  Anthony Miranda Vieira ,  Peterson Almeida ,  Sergio Varga

IPC: G06F17/00 ,  H04L51/02 ,  G06F40/226 ,  G06F11/36 ,  G06F16/36 ,  G06F16/35 ,  G06F40/242

Abstract: A computer-implemented method, computer system, and computer program product for for generation of a chatbot. The method may include receiving data in a first format. The method may include generating one or more clusters from the received data. The method may include labeling the generated one or more clusters. The method may include exporting the one or more labeled clusters into a cluster database. The method may include generating the chatbot using the one or more labeled clusters exported from the cluster database. The method may include executing a validation script into the chatbot to generate a report. The method may include receiving a determination on an accuracy of the chatbot based on the generated report. In response to determining that the chatbot is not accurate, the method may include determining whether a manual adjustment directly on the chatbot is needed.

公开(公告)号：US11472120B2

公开(公告)日：2022-10-18

申请号：US16868889

申请日：2020-05-07

Applicant: Kyndryl, Inc.

Inventor： Sergio Varga ,  Sarbajit K. Rakshit ,  Daniela Trevisan

IPC: B29C64/393 ,  B33Y50/02 ,  B33Y30/00 ,  B29C64/264 ,  B33Y10/00 ,  B29C64/135

Abstract: Aspects of the present disclosure relate to light-based 3D printing. A computer aided design (CAD) representation of an object is obtained. Mirror and lighting requirements of a light-based 3D printer containing at least one mirror and at least one light source are determined based on the CAD representation of the object. Mirror and lighting characteristics of the at least one mirror and the at least one light source are adjusted based on the determined mirror and lighting requirements, the adjusting resulting in a first 3D light-based printer configuration. A 3D printing process is then initiated, wherein initiating the 3D printing process includes exposing a photosensitive material within the light-based 3D printer to light based on the first light-based 3D printer configuration.

公开(公告)号：US20220164645A1

公开(公告)日：2022-05-26

申请号：US17102695

申请日：2020-11-24

Applicant: KYNDRYL, INC.

Inventor： FABIO ZANFORLIN ZAINA ,  Leonardo de Bem Ferreira ,  Silvana Galeazzi ,  Marco Antonio Milanez ,  Sergio Varga ,  Thiago Bianchi

IPC: G06N3/08 ,  G06F8/65 ,  G06N3/04 ,  G06F16/245

Abstract: A method and a system for automating security updates in a multi-tiered architecture of a system environment. The method includes receiving a software update note relating to a multi-tiered architecture system environment and determining a patch in the software update note is initially compatible with the system environment. The method also includes predicting, by a patch acceptance machine learning model, the patch is patchable within in the system environment and predicting, by an installation machine learning model, an installation patch time for the patch on the system environment. The method also includes installing the patch at the installation patch time on the system environment, and validating the patch installation using a validation machine learning model.

公开(公告)号：US20220101860A1

公开(公告)日：2022-03-31

申请号：US17035736

申请日：2020-09-29

Applicant: KYNDRYL, INC.

Inventor： Sergio Varga ,  Sarbajit K. Rakshit ,  Daniela Trevisan

IPC: G10L17/22 ,  G10L17/04 ,  G06N20/00

Abstract: Computer-generated speech based on a device feed includes generating a corpus for robotic use by receiving first information representative of a user's speech in different environments at different times and second information representative of environmental conditions of different locations at the different times. The first and second information of corresponding different environments and different locations for each of the different times is combined with third information received from external data sources. A plurality of annotated combined datasets including the first information, the second information, and the third information is generated for each of the different times in a repository. The plurality of annotated combined datasets is correlated to create training data that is subsequently processed using a predetermined machine learning model. A correlation among spoken tone associated with a contextual situation based on skills of the user is identified in the training data and used to update the corpus.