International Business Machines Corporation

Kyndryl, Inc.

International Business Machines Coproration

Jeremy R Fox

Sarbajit Kumar Rakshit

Zachary A Silverstein

Kelley Anders

Michael Bender

Liam S Harpur

Gregory J Boss

Shikhar Kwatra

Jonathan D Dunne

Tushar Agrawal

Mauro Marzorati

Trudy L Hewitt

Craig M Trim

Jacob Ryan Jepperson

Lisa Seacat DeLuca

Martin G Keen

Clement Decrop

Fang Lu

Andrew R Jones

Christian Compton

John Elbert Moore, Jr

Spencer Thomas Reynolds

Kulvir Singh Bhogal

Todd Russell Whitman

Atul Mene

Logan Bailey

Jeremy A Greenberger

Jana Helton Jenkins

John David Wilson

John Rice

Grant Douglas Miller

Melanie Dauber

Rick A Hamilton, Ii

Uri Kartoun

Jennifer M Hatfield

Kevin Charles Mcconnell

Cesar Augusto Rodriguez Bravo

Raghuveer Prasad Nagar

Brian M O'Connell

Aaron K Baughman

Rhonda L Childress

Robert Huntington Grant

Gary Francis Diamanti

Stan Kevin Daley

Tiberiu (Jim) Suto

Jill S Dhillon

Alexander Reznicek

Su Liu

Bahman Hekmatshoartabari

Maharaj Mukherjee

Charles Evan Beller

Randy Allan Rendahl

Paul N Krystek

Natalie Brooks Powell

Manjunath Ravi

Carolina Garcia Delgado

Chris Kau

Nadiya Kochura

Sushain Pandit

Adam Lee Griffin

Mary E Rudden

Thomas Jefferson Sandridge

Hamid Majdabadi

Corville O Allen

Christopher J Hardee

Dana Lea Price

Ching-Yun Chao

Michael C Hollinger

Indervir Singh Banipal

Christian Benjamin Kau

Kyle Gene Brown

John Michael Ganci, Jr

Peeyush Jaiswal

Sarvesh S Patel

Jonathan Lenchner

Kushal S Patel

Mark Patrick Delaney

David Bruce Lection

Hernan A Cunico

Florian Pinel

Jun Su

Mark B Stevens

Vinod A Valecha

Hemant Kumar Sivaswamy

Alexandre Polozoff

Abhishek Jain

Mu Qiao

Gary Denner

Todd P Seager

Sumit Patel

Priyansh Jaiswal

Ping Xiao

Ann Corrao

Shubhadip Ray

Pratyush Kumar

Barton Wayne Emanuel

Mickey Iqbal

Jagadesh Ramaswamy Hulugundi

Shilpa Shetty

Venkata Vishwanath Gadepalli

The illustrative embodiments provide for adaptation of reference architecture documents across clouds. An embodiment includes loading a reference architecture document. The embodiment also includes populating a knowledge repository corpus where the knowledge repository corpus includes data from information technology (IT) products, cloud services, and integrations stored with associated metadata about functionalities. The IT products, the cloud services, and the integrations are stored with metadata. The embodiment also includes classifying, using an incident analysis module, the service incidents based on the reference architecture document. The embodiment also includes detecting flaws in the reference architecture document based on the classified service incidents. The embodiment also includes creating a weighted graph of the cloud services. The embodiment also includes traversing the weighted graph and creating an adapted reference architecture based on the traversed weighted graph.

Adaptation of reference architecture documents across clouds

A computer-implemented method, a computer system and a computer program product automatically generate product videos based on requested feature sets in stored data. the method includes acquiring a plurality of product features from a server, where each product feature in the plurality of product features is associated with data selected from a group consisting of: text data, audio data, and image data. The method also includes receiving a request for a product video, where a product in the product video comprises a set of product features in the plurality of product features. The method further includes identifying the data associated with each product feature in the set of product features for the request. Lastly, the method includes generating the product video based on identified data for the product.

Generation of product videos using machine learning

A computer-implemented method, a computer system and a computer program product generate a query response in an environment based on predicted relationships between users. The method includes capturing a question with a device in the environment, where the question includes a speaking voice and is selected from a group consisting of: video data, audio data and text data. The method also includes identifying the speaker of the question based on the speaking voice. The method further includes determining a relationship between the question and each user interaction in a database of user interactions, where each user interaction is associated with a user. In addition, the method includes selecting a response from the database of user interactions based on the relationship. Lastly, the method includes transmitting the response to the speaker of the question in the environment, where the transmission of the response uses a voice of the user.

Relationship-driven virtual assistant

An approach for enhancing retrieval of drill through data is provided. A determination is made as to whether a source report generated from query results of a query by a user contains a data item that is associated with drill through data. In response to a positive determination, a data drill MetadataBot (DDMB) is initiated. In response to activation, the DDMB searches metadata associated with the query results to identify a set of DDMB parameters for the data item. These DDMB parameters can include the cell that contains the data item and a target report containing the drill through data for the cell. Based on this search, the DDMB generates an augmented report that contains a visual identifier for the drill through data-associated cell, allowing the user to retrieve the target report by interacting with the visual identifier.

Artificial intelligence based bot-enhanced retrieval of drill through data

A processor may receive an object dataset based on an object. The processor may generate an interactive model of the object to display to a user using the object dataset. The processor may receive an interaction dataset associated with the user interacting with the interactive model. The processor may analyze the interactive data to identify one or more modifications to the one or more parameters of the object, based on the user interacting with the interactive model.

Object modification in a smart environment

An embodiment for dynamically converting a virtual reality (VR) classroom into a VR breakout session is provided. The embodiment may include receiving educational content from a VR educational session and profiles of a plurality of users. The embodiment may also include identifying a topic of the educational content. The embodiment may further include extracting a plurality of real-world use cases relevant to the identified topic from a knowledge corpus. The embodiment may also include in response to determining at least two users have at least one overlapping learning preference, dividing the at least two users into a subgroup. The embodiment may further include converting the VR educational session into a smaller VR breakout session containing at least one real-world use case conforming to the at least one overlapping learning preference. The embodiment may also include displaying the converted VR educational session to the at least two users in the subgroup.

Dynamic conversion of VR classroom into VR breakout session

Mitigating GPS inaccuracy is provided. The method comprises identifying a required level of location accuracy for an activity of an autonomous system and determining, according to GPS coordinates, a location of the autonomous system. A determination is made, according to a knowledge base created by historical learning, whether GPS location accuracy at the location of meets the required level of location accuracy for the activity. Responsive to a determination that the GPS location accuracy at the location of the autonomous system does not meet the required level of accuracy, location determination is handed off to an installed infrastructure within proximity of the autonomous system which provides the required level of location accuracy. The autonomous system then performs the activity according to location information provided by the installed infrastructure.

Proactive mitigation of GPS accuracy errors

A system for layer-by-layer three-dimensional (3D) printing of a 3D printed object. The system includes a printing component configured to print a plurality of layers to form the 3D printed object, a surface modification component configured to be co-operable with the printing component and configured to apply an appropriate degree of surface roughness to at least one of the plurality of layers after being printed, and a controller configured to identify parameters of each of the at least one of the plurality of layers and configured to control operation of the printing component and the surface modification component, wherein the parameters include the appropriate degree of surface roughness.

Method and system of three-dimensional printing to prepare surface for gripping of subsequent layers

Methods for intelligent management of asset workflows are disclosed herein. One method includes predicting that a user is going to perform a predetermined action based on one or more user movements included in a signal received from a wearable sensing device and generating, by a processor, a warning of one or more consequences of the user performing the predetermined action. The method further includes displaying, on augmented reality glass, the warning to the user prior to the user actually performing the predetermined action. Also disclosed herein are systems and apparatus that can include, perform, and/or implement the operations of the methods.

Systems, apparatus, program products, and methods for intelligent management of asset workflows

A method, a structure, and a computer system for playback optimization. The exemplary embodiments may include transcribing an audio stream at normal and at high playback speed, as well as determining whether portions of the audio stream are unintelligible at the high playback speed. The exemplary embodiments may further include reducing a speed of the high playback speed for portions determined unintelligible, and transcribing the audio stream with the unintelligible portions played at the reduced high playback speed. The exemplary embodiments may further include determining whether the unintelligible portions are still unintelligible at the reduced high playback speed and, if not, identifying the reduced high playback speed as an optimal playback speed of the unintelligible portions. The exemplary embodiments may additionally include, in response to receiving a request to play the audio stream at the high playback speed, playing the unintelligible portions at the optimal playback speed.

Audio playback and captioning

According to an embodiment of the present invention, a method for detecting allergens using smart tooth and IoT is provided. The method includes obtaining real-time environmental allergen context data, wherein the obtained real-time environmental allergen context data includes visual data and sensor data. Features are extracted from the obtained real-time environmental allergen context data, including at least one detected environmental allergen type, an environmental allergen exposure pathway, and an environmental allergen concentration. A real-time unique allergic reaction risk score is generated for a user based on analysis of a user allergic risk profile and the extracted features from the obtained real-time environmental allergen context data. A real-time warning is generated to the user when the generated unique allergic reaction risk score exceeds a predetermined threshold.

Detecting allergens using internet of things

A cane for increased sweep coverage includes a first time-of-flight (TOF) sensor, a haptic feedback generator and a processor. The first TOF sensor is disposed at a first end of the cane and is configured to emit a first TOF beam. The haptic feedback generator is disposed towards a second end of the cane that is distally opposite from the first end of the cane. The processor is configured to receive signal data from the first TOF sensor, determine, based on the received signal data, whether an obstacle is present within the first TOF beam, and activate the haptic feedback generator in a first haptic feedback pattern in response to the processor determining that the obstacle is present. A method for using the cane to detect obstacles is also provided.

Wide sweep cane

An embodiment for improved authentication of chatbot users for chat history recovery. The embodiment may record a first chat conversation between a first chat service operator and a first user, wherein the first chat conversation includes a first-step authentication and a chat history. The embodiment may detect a request to resume the first chat conversation. The embodiment may, in response to detecting the request to resume the first chat conversation, initiate a recovery process by sending a random-generated token to the first-step authentication. The embodiment may receive verification of the random-generated token. The embodiment may generate, by a large language model, one or more authentication questions based on content of the chat history. The embodiment may authenticate the first user based on one or more correct answers to the one or more authentication questions. The embodiment may resume the first chat conversation including the chat history.

Cross-platform chatbot user authentication for chat history recovery

According to one embodiment, a method, computer system, and computer program product for iteratively improving a virtual model of an object to be printed in a mixed reality environment is provided. The present invention may include rendering the virtual model within the mixed-reality environment; monitoring interactions between a user and the virtual model within the mixed-reality environment; predicting one or more deficiencies in the physical object based on the monitoring; suggesting one or more edits of the virtual model to the user to address the one or more predicted deficiencies; and integrating the one or more edits into the virtual model.

Iterative virtual reality modeling amelioration for three-dimensional to-be-printed objects and virtual reality filament sections

An approach for improving completely automated public turing test to tell computers and humans apart (CAPTCHA) reliability for a resource. The approach receives a request for a CAPTCHA validation from a user. The approach retrieves a CAPTCHA analysis configuration associated with the user. The approach displays a CAPTCHA multi-zone display defined by the configuration. The approach receives video input containing adjunct objects, associated with objects visible on the user, from the user for the multi-zone display. The approach determines if the inputs are valid based on the CAPTCHA analysis configuration. The approach, responsive to the inputs being valid, allows access to the resource.

Multi-factor captcha with adjunct signals

Growing community of inventors

Georgetown, TX, United States of America

Jeremy R Fox