International Business Machines Corporation

Kyndryl, Inc.

Accenture Global Solutions Limited

Nuance Communications, Inc.

Airbnb, Inc.

Kuntal Dey

Seema Nagar

Roman Vaculin

Enara C Vijil

Sougata Mukherjea

Pramod Vadayadiyil Raveendran

Karan Ahuja

Manish Anand Bhide

Sudhanshu Shekhar Singh

Sarbajit Kumar Rakshit

Vijay Ekambaram

Sameep Mehta

Swati Rallapalli

Willie L Scott, Ii

Saritha Arunkumar

Nizar Lethif

Pramod Verma

Rachel Leekin

Danish Contractor

Saiprasad Kolluri Venkata Sesha

Nishtha Madaan

Vikrant Shyamkant Kaulgud

Pradipta De

Charu Pandhi

Sreekanth L Kakaraparthy

Vinayak Sastri

Srikanth Govindaraj Tamilselvam

Amit Anil Nanavati

Venkatraman Ramakrishna

Abhijit Mishra

Natwar Modani

Dipyaman Banerjee

Jitendra Singh

Prateek Goyal

Utkarsh Dwivedi

Jayakarthik Jayabalan

Vijay A Kumar

Diptikalyan Saha

Puthukode G Ramachandran

Vikas Agarwal

Sumit Mittal

Adam Patten Burden

Mukul Tewari

Nitendra Rajput

Arun Kumar

Vibhu Saujanya Sharma

Mohit Jain

James David Cleaver

Kapil Singi

Pranay Kumar Lohia

Michael James McGuire

Madhavi Katari

Josephine E Justin

Thuy Luong

Sushain Pandit

Biplav Srivastava

Sanjay Podder

Girish Dhanakshirur

Hima Patel

Aniya Aggarwal

Alwyn R Lobo

Rakesh Rameshrao Pimplikar

Lisa Seacat DeLuca

Shikhar Kwatra

Jonathan D Dunne

Jeremy A Greenberger

Tamer E Abuelsaad

Mukesh Kumar Mohania

Charles Daniel Wolfson

Malolan Chetlur

Padmanabha Venkatagiri Seshadri

Amith Singhee

Ashok Pon Kumar Sree Prakash

Muhammed Fatih Bulut

Janardan Misra

Constantin Mircea Adam

L Venkata Subramaniam

Milton H Hernandez

Pratyush Kumar

Arvind Agarwal

Anupam Jain

Neville Dubash

Venkatesh K Subramanian

Rema Ananthanarayanan

Nataraj Kuntagod

Pooja Aggarwal

Saneem Ahmed Chemmengath

Seep Goel

Venkateswara Reddy Madduri

Nikhil Jain

Naveen Panwar

Anush Sankaran

Inkit Padhi

Abhishek Shah

Deepak Vijaykeerthy

Senthil Kumar Kumaresan

Emily A Ray

Prateeti Mohapatra

Andrea Maria Milazzo

Samarth Sikand

A method for detection of a corrupted sensor including providing a first sensor; identifying one or more correlating sensors to the first sensor; determining a correlation between the first sensor and the correlating sensors according to historical sensor values; obtaining a calculated value of the first sensor based on values of the correlating sensors and the correlation; obtaining a measured value of the first sensor; and determining whether the first sensor is corrupted according to a difference between the calculated value and the measured value of the first sensor.

Corrupted sensors detection in sensor consortium

A data performance measurement of a computer system is measured. A future value of the data performance measurement is forecasted by executing a forecasting model. A set of throughput model input parameters is configured. A throughput requirement for the computer system is computed by executing a throughput model using the set of throughput model input parameters and the future value of the data performance measurement. A capacity requirement corresponding to the throughput requirement is determined. A resource within the computer system is deployed according to the capacity requirement.

Throughput based sizing for hive deployment

A method includes receiving, by a computing device, concepts of a domain; determining, by the computing device, objects relevant to the concepts; generating, by the computing device, a new image by stitching the relevant objects together; determining, by the computing device, whether the new image is accurate or inaccurate; and in response to determining the new image is inaccurate, propagating, by the computing device, the inaccurate new image back to a convolutional neural network (CNN).

Object stitching image generation

A method and system for assisting program code development are disclosed. The method may include obtaining multimodal data of a meeting discussing a program code development, extracting a plurality of topics and a plurality of concepts from the multimodal data, identifying a plurality of meeting segments for the plurality of concepts. The method may further include determining a coding intent from program codes for the program code development, aligning the coding intent to a set of topics, identifying the set of concepts associated with the topic aligned with the coding intent, identifying a set of meeting segments associated with the concept. The method may further include determining an alignment metric of the meeting segment based on an alignment metric between the coding intent and the topic, and outputting one or more meeting segments for the coding intent based on alignment metrics of the one or more meeting segments.

Assisting program code development by processing multimodal data of a meeting

Aspects of the present invention disclose a method, computer program product, and system for management and usage of shared authentication credentials. The method includes one or more processors updating usage information associated with an authentication credential with a media access control address (MAC address) that corresponds to a computing device that corresponds to using the authentication credential. The method further includes one or more processors receiving a login request that includes the authentication credential from a computing device. The method further includes one or more processors fetching a MAC address of the computing device that sent the login request. The method further includes one or more processors validating the authentication credentials and the MAC address.

Management of shared authentication credentials

Disclosed herein is a system and method for generating computer code for a plurality of components of a software development project. An artificial intelligence code generator can generate computer code in response to a natural language text input describing a component of the software development project. A first database can store natural language text describing components of the software development project. A second database can store computer code generated at least partially by the artificial intelligence code generator and defining components of the software development project and corresponding to the natural language text stored in the first database. Using a pre-trained language model, the system can generate a natural language summary text based on the code intent of the first component, the identified characteristics of the objects, and the natural language text retrieved from the first database.

Computer code generator

A system and associated methods that enable social media representation and collaboration platform of enterprise information technology (IT) components that enables human-to-human, human-to-machine and machine-to-machine communications to help easily understand the set of enterprise IT components, its configuration(s), its intra/inter relationship(s), better navigation and visibility across various related components, and augmenting system troubleshooting.

Social media representation and collaboration platform for enterprise it

Provided is a method, system, and computer program product for storing images across multiple distributed computing systems according to image sensitivity. The method comprises identifying an image and analyzing the image to identify sensitive information in the image. The method further comprises splitting the image into a sensitive portion and a non-sensitive portion. The method further comprises storing the sensitive portion of the image in a first distributed computing system and storing the non-sensitive portion of the image in a second distributed computing system.

Image storage across distributed computing systems

An embodiment includes identifying a robot that is available to perform a task involving an asset in a data center. The embodiment transmits a script to the robot that includes commands corresponding to actions to be executed by the robot in performing the task and transmits a dispatch command to the robot configured to enable the robot to travel from a robot resting place to the asset to begin the task. The embodiment relays a verification request received from the robot after the robot has completed a portion of the task to the vendor. The embodiment also relays, responsive to the verification request, an updated script based on updated instructions from the vendor for dynamically modifying the task to correcting an irregularity. The embodiment transmits, responsive to completion of the task, a recall command to the robot configured to enable the robot to travel from the asset to the robot resting place.

Managing shared robots in a data center

Method, apparatus, and computer program product are provided for estimating crop pest risk and/or crop disease risk at sub-farm level. In some embodiments, a farm region is determined based on farm definition data, and input data associated with the farm region are retrieved from a plurality of data sources. The input data may include a plurality of pixel sets. In some embodiments, for each pixel set, crop risk data are determined based on the input data using one or more spatiotemporal regression models. The crop risk data may include an estimate of crop pest risk and/or crop disease risk for each pixel set. In some embodiments, the farm region is categorized into a plurality of sub-farms each defining a risk level category for that sub-farm based on the crop risk data. In some embodiments, the sub-farms are displayed as a visual heat-map, along with recommended antidote options.

Estimation of crop pest risk and/or crop disease risk at sub-farm level

An unmanned vehicle includes a body, a propulsion system connected to the body, a computing system connected to the body, and a display connected to an exterior of the body and electrically connected to the computing system. In addition, the computing system is configured to dynamically change the appearance of the display during operation of the unmanned vehicle.

Differentiating unmanned vehicles by changing exterior appearance

Social media representation and collaboration platform for enterprise IT

Embodiments are disclosed for a method. The method includes receiving an annotation set for a machine learning model. The annotation set includes multiple data points relevant to a task for the machine learning model. The method also includes determining total weights corresponding to the data points. The total weights are determined based on multiple ordering constraints indicating multiple data classes and corresponding weights. The corresponding weights represent a relative priority of the data classes with respect to each other. The method further includes generating an ordered annotation set from the annotation set. The ordered annotation set includes the data points in a sequence based on the determined total weights.

Ordering annotation sets for machine learning

Provided is a method, computer program product, and system for automatically assigning robotic devices to users based on need using predictive analytics. A processor may monitor activities performed by one or more users. The processor may determine, based on the monitoring, a set of activities that require assistance from a robotic device when being performed by the one or more users. The processor may match the set of activities to a set of capabilities related to a plurality of robotic devices. The processor may identify, based on the matching, a first robotic device that is capable of assisting the one or more users in performing a first activity of the set of activities. The processor may deploy the first robotic device to assist the one or more users in performing the first activity.

Assignment of robotic devices using predictive analytics

Methods, computer program products, and systems are presented. The methods include, for instance: training of a machine learning model for predicting a rating in certain content rating systems based on training data. The machine learning model includes a plurality of maturity classifiers corresponding to individual features of the previously rated contents. An input content is obtained and features of the input content are extracted by use of respective content analysis tools and subsequently classified by the maturity classifiers of the machine learning model.

Dynamic content rating assistant

Growing community of inventors

New Delhi, India

Kuntal Dey