International Business Machines Corporation

Kyndryl, Inc.

Lenovo (singapore) Pte. Ltd.

Other

Maplebear Inc.

Lenovo Enterprise Solutions (singapore) Pte. Ltd.

Sarbajit Kumar Rakshit

John Michael Ganci, Jr

James Edward Bostick

Martin G Keen

Craig M Trim

Jeremy R Fox

Venkata Vara Prasad Karri

Eric Vance Kline

Shikhar Kwatra

Barry Alan Kritt

Vijay Ekambaram

Tushar Agrawal

Raghuveer Prasad Nagar

Sathya Santhar

Shailendra Moyal

Saraswathi Sailaja Perumalla

Kimberly Greene Starks

Sudheesh S Kairali

John David Wilson

Akash U Dhoot

Zachary A Silverstein

Michael Bender

Mauro Marzorati

Christopher J Hardee

Cesar Augusto Rodriguez Bravo

Aaron K Baughman

Gregory J Boss

David Bruce Lection

Gary David Cudak

Mukundan Sundararajan

Mark B Stevens

Robert Huntington Grant

Keith R Walker

John Elbert Moore, Jr

Komminist S Weldemariam

Sushain Pandit

Fang Lu

Todd Russell Whitman

Kuntal Dey

Hernan A Cunico

Adam Roberts

Harish Bharti

Vijay Kumar Ananthapur Bache

Hemant Kumar Sivaswamy

Abhishek Jain

Sandeep R Patil

Katsuyuki Sakuma

Soma Shekar Naganna

Liam S Harpur

Gandhi Sivakumar

Maharaj Mukherjee

Jana Helton Jenkins

Brian Samuel Beaman

Edgar Adolfo Zamora Duran

Jeremy A Greenberger

Vittorio R Castelli

Sasikanth Eda

Randy Allan Rendahl

James R Kozloski

Kulvir Singh Bhogal

Michael S Gordon

Donna Karen Byron

Seema Nagar

Kelley Anders

Manish Anand Bhide

Swaminathan Balasubramanian

Chandrasekhar Narayanaswami

Sougata Mukherjea

Clifford A Pickover

Jonathan D Dunne

Peeyush Jaiswal

Nitin Gaur

Nadiya Kochura

Florian Pinel

Romelia H Flores

Vinod A Valecha

Petr Novotny

Marc Henri Coq

Jeronimo Irazabal

Michael K Gschwind

Lisa Seacat DeLuca

Valentina Salapura

Rhonda L Childress

Trudy L Hewitt

Sarvesh S Patel

Manish Satyapal Gupta

Jonathan Lenchner

Kushal S Patel

James Peter Ward

Nataraj Nagaratnam

David Jaramillo

John A Gunnels

Srikanth Govindaraj Tamilselvam

Pankaj Satyanarayan Dayama

Rajesh Kumar Saxena

Alexandre Polozoff

Justin David Weisz

Diwesh Pandey

Michael John Spisak

Vincenzo V Di Luoffo

Systems and methods are provided for detecting and repelling bird species approaching a wind farm, using targeted ultrasonic/sonic frequencies. A zone of vulnerability boundary is set around the wind farm at which bird repellers start responding to instructions to broadcast ultrasonic/sonic. Based on the received plurality of images, at least one bird species is identified as approaching the zone of vulnerability boundary. The bird repellers receive instructions to broadcast beginning with the calculated starting ultrasonic/sonic frequency, and incrementally increasing or decreasing the starting ultrasonic/sonic frequency in response to the at least one identified bird species continuing to approach or to move away from the zone of vulnerability boundary. A learning model is updated with statistics, which the identified plurality of bird species and the ultrasonic/sonic frequency receiving the optimal response from the identified plurality of bird species.

Automated bird detection and targeted activation of ultrasonic bird repeller for wind turbines

A computer-implemented method for multimedia modification is disclosed. The computer-implemented method includes classifying one or more objects detected within a user's field of view through an augmented reality environment. The computer-implemented method further includes determining a context of the user based, at least in part, on the one or more classified objects detected within the user's field of view. The computer-implemented method further includes generating a priority score for the one or more classified objects based, at least in part, on the context of the user. The computer-implemented method further includes modifying an object detected within the user's field of view based, at least in part, on the priority score of the object.

Contextual priority based multimedia modification

A computer-implemented method according to one embodiment includes identifying a load that will be applied to a robotic structure, and determining whether the load, when applied to the robotic structure, would exceed a structural threshold of the robotic structure. In response to determining that the load, when applied to the robotic structure, would exceed the structural threshold, a position of one or more swarm robots with respect to the robotic structure is determined that would increase a structural strength of the robotic structure, and the one or more swarm robots are caused to assume the determined position. A computer program product according to another embodiment includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Increasing strength of a robotic structure using swarm robot(s)

An approach for adjusting an inclination angle of a mirror to maximize power output of an adjacent solar panel and shadow-effect energy generator (SEG). The approach retrieves data associated with a solar irradiance profile and a SEG shadow profile. The approach predicts an irradiance profile based on the data. The approach predicts a shadow contrast ratio based on the data. The approach predicts a SEG shadow profile based on the data. The approach calculates optimized control parameters associated with a mirror based on the irradiance profile, the shadow contrast ratio and the SEG shadow profile. The approach adjusts the mirror inclination angle based on the optimized control parameters.

Maximizing solar panel power generation with shadow energy generation

Described are techniques for appropriately gripping objects by robots. A target object (e.g., circuit board) is identified to be gripped by a robotic arm of a robot, such as a robot in an industrial facility. Upon identifying the target object to be gripped by the robotic arm, the attributes of the target object are determined. One or more pores of the robotic arm may then be selected to be enabled to secrete an adhesive based on the attributes of the target object. Furthermore, the adhesion level corresponding to the amount of the adhesive to be secreted by the selected pores of the robotic arm is determined based on the attributes of the target object. The selected one or more pores of the robotic arm are then activated to secrete the adhesive according to the adhesion level in order to appropriately grip the target object by the robotic arm.

Appropriately gripping objects by robots

The exemplary embodiments disclose a method, a computer program product, and a computer system for managing user commands. The exemplary embodiments may include a user giving one or more commands to one or more devices, collecting data of the one or more commands, extracting one or more features from the collected data, and determining which one or more of the commands should be executed on which one or more of the devices based on the extracted one or more features and one or more models.

Augmented reality enabled command management

A processor may receive first object data associated with a first object to be transported. The processor may receive vehicle data associated with one or more potential vehicles for transportation of the first object. The processor may receive context data associated with a context for the transportation of the first object. The processor may simulate the transportation of the first object utilizing each of the one or more potential vehicles using digital twin simulation. The processor may select a first vehicle of the one or more potential vehicles based on an optimization of an optimization factor associated with an outcome of the digital twin simulation.

Digital twin simulation for transportation

According to one embodiment, a method, computer system, and computer program product for digital image enhancement is provided. The embodiment may include receiving a digital image being navigated by a user. The embodiment may include identifying an image content navigation pattern of the user and a context of the digital image. Based on the image content navigation pattern and context, the embodiment may include identifying one or more objects of the digital image on which the user will perform a predicted zoom-in action. The embodiment may include identifying one or more distributed computing resources for digital image enhancement of the identified one or more objects. The embodiment may include performing digital image enhancement of the identified one or more objects. Upon the user performing a zoom-in action on an identified object which matches a predicted zoom-in action, the embodiment may include displaying a digitally enhanced image of the identified object.

Generative adversarial network based digital image enhancement through distributed resources

A computer-implemented method for predicting a next frame for a video is provided. Aspects include obtaining the video having a sequence of frames, obtaining a plurality of machine learning models (MLMs) that are trained to perform next frame prediction, and inputting a subset of the sequence of frames into each of the plurality of MLMs. Aspects also include calculating, for the subset of the sequence of frames, a score for each of the plurality of MLMs and generating, using one of the plurality of the MLMs having a highest score, the next frame, where the next frame is a frame immediately subsequent to the subset of the sequence of frames.

Predicting a next frame for a video using ensembling

Managing a package delivery system deploying an unmanned vehicle including an inflatable unit for reducing package vibration in a transportation vehicle. Package data is received at a computer, and the package data includes package descriptions. Spatial positioning of the packages in the transport space is tracked to determine, spatial positioning changes between the packages in the transport space based on the package data received at the computer and the transport. One or more unmanned vehicles are delivered to the transport space based on the spatial positioning changes in the transport space, and the unmanned vehicles including inflatable units. The inflatable units are deployed in the transport space by inflating the inflatable units at locations in the transport space based on the spatial positioning changes to discourage package movement in the transport space.

Reducing package vibration during transportation by initiating mobile vehicles based on computer analysis

A computer hardware system associated with a hybrid cloud including a private cloud and a public cloud has a hardware processor configured to perform the following executable operations. A plurality of data sets of unprocessed data is randomly sampled to generate a plurality of random samples respectively associated with each of the plurality of data sets. The plurality of random samples is pre-processed, using a machine learning engine, to identify hidden correlations contained therein. The hidden correlations are evaluated against a confidentiality model to characterize each of the plurality of segments as to confidentiality. The data sets are segmented by assigning the data sets to one of the private cloud or the public cloud based upon the evaluating. Data sets assigned to the private cloud based upon the segmenting are processed using the private cloud.

Segmentation of data in hybrid cloud

Disclosed are techniques to determine navigation paths for mobile points of consumption of edge computing resources where the edge computing resources are at least partially hosted on satellite devices. Datasets corresponding to a set of edge computing satellites are received describing their positions, orbital paths, and edge computing resources. Further datasets are received corresponding to mobile points of consumption of edge computing resources. Using both datasets, predictions are determined corresponding to demand for edge computing resources of the edge computing satellites. When a new mobile point of consumption of edge computing resources queues up a transit route to a destination, that transit route and the accompanying requirement for edge computing resources is compared with the determined predictions of resource availability. Where sufficient edge computing resources are unavailable for a transit route, a new route is generated to transit through regions where sufficient edge computing resources are predicted to be available.

Transit routes with orbital edge computing resource availability for mobile edge computing consumption points

An embodiment for transmitting and regenerating compressed media is provided. The embodiment may include receiving an image selected by a sender to be transmitted. The embodiment may also include sending the image to a pre-trained generative adversarial network (GAN) model. The embodiment may further include identifying a first set of one or more pixels in the image assigned to one or more high priority Class of Service (CoS) groups and a second set of one or more pixels in the image assigned to one or more low priority CoS groups. The embodiment may also include compressing the one or more pixels in the second set. The embodiment may further include transmitting the one or more pixels in the first set and the compressed one or more pixels in the second set to a recipient in an order from a highest priority CoS group to a lowest priority CoS group.

Compressed media transmission and high quality regeneration

A computer-implemented method, according to one embodiment, includes dynamically assigning reputation scores to a plurality of tasks, and dynamically assigning reputation scores to a plurality of edge nodes. The method further includes dynamically placing the tasks into the edge nodes based on the reputation scores assigned to the tasks and the reputation scores assigned to the edge nodes. A computer program product, according to one embodiment, includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method. A system, according to another embodiment, includes a processor, and logic integrated with the processor, executable by the processor, or integrated with and executable by the processor. The logic is configured to perform the foregoing method.

Dynamically placing tasks into edge nodes based on reputation scores

A computer-implemented method, a computer system, and a computer program product are provided. A first computer receives first data from a first sensor associated with a first user. The first computer uses artificial intelligence to generate a first recommendation for a replacement object for the first user. The generating is based on the first data. The first recommendation indicates ability of the replacement object to replace a first object associated with the first user. The first computer transmits the first recommendation for presentation to the first user.

Artificial intelligence-generated suggestion for item replacement

Growing community of inventors

Kolkata, India

Sarbajit Kumar Rakshit