Patents by Inventor Veenu Arora
Veenu Arora has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11875243Abstract: Methods, systems, and computer-readable storage media for receiving, by an aromatic simulation platform, a recipe including descriptions indicative of ingredients of a consumable, processing the recipe through a first neural network to provide a recipe embedding, processing an ingredients profile to determine an aroma compounds profile representing the ingredients of the ingredients profile, processing the aroma compounds profile through a second neural network to provide an aroma embedding, and processing the recipe embedding and the aroma embedding through a third neural network to provide an aroma profile representative of the consumable of the recipe.Type: GrantFiled: January 11, 2022Date of Patent: January 16, 2024Assignee: Accenture Global Solutions LimitedInventors: Alpana A. Dubey, Veenu Arora, Nitish A. Bhardwaj, Aakanksha Saini
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Publication number: 20230222321Abstract: Methods, systems, and computer-readable storage media for receiving, by an aromatic simulation platform, a recipe including descriptions indicative of ingredients of a consumable, processing the recipe through a first neural network to provide a recipe embedding, processing an ingredients profile to determine an aroma compounds profile representing the ingredients of the ingredients profile, processing the aroma compounds profile through a second neural network to provide an aroma embedding, and processing the recipe embedding and the aroma embedding through a third neural network to provide an aroma profile representative of the consumable of the recipe.Type: ApplicationFiled: January 11, 2022Publication date: July 13, 2023Inventors: Alpana A. Dubey, Veenu Arora, Nitish A. Bhardwaj, Aakanksha Saini
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Patent number: 11531948Abstract: The disclosed system and method provide a way to create, update, and execute dynamic goal plans. Updating a dynamic goal plan may be based on the initial sequence of actions of the goal plan as well as the corresponding states of the actions. By using a sequence to sequence model, a goal plan can still be processed when the length of the input (initial sequence of actions) differs from the length of the output (updated sequence of actions). A sequence to sequence model can determine the interdependencies between actions that can contribute to the optimal order in which actions can efficiently be performed. A single layer neural network or clustering can be used to approximate the state of a goal plan that may be capable infinite states. This approximation improves accuracy in capturing the state of a goal plan, thereby improving accuracy in predicting the future state of a system, which can help with planning (e.g., gathering resources in advance).Type: GrantFiled: February 19, 2020Date of Patent: December 20, 2022Assignee: Accenture Global Solutions LimitedInventors: Alpana Dubey, Kumar Abhinav, Sakshi Jain, Veenu Arora
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Patent number: 11507802Abstract: The present disclosure relates to a system, and method for computer-based recursive learning of artificial intelligence (AI) apprentice agents. The system includes a system circuitry in communication with a database and a memory. The system circuitry is configured to receive a new data-structure comprising one or more inputs and a goal, and convert, using a perception agent, the one or more inputs of the new data-structure into one or more input feature parameters of the new data-structure. The system circuitry is configured to obtain, using a reasoning agent, an action for the new data-structure, and determine, using an evaluation agent, whether the action for the new data-structure generates the goal of the new data-structure. When it is determined that the action generates the goal of the new data-structure, the system circuitry is further configured to store the new data-structure in the database.Type: GrantFiled: August 30, 2019Date of Patent: November 22, 2022Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Kumar Abhinav, Alpana Dubey, Sakshi Jain, Veenu Arora, Hindnavis Vijaya Sharvani
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Patent number: 11321887Abstract: Examples of article designing are described herein. In an example, image data, margin data, and sales data corresponding to a plurality of articles may be obtained. The obtained data may be analyzed to identify a first article image of a first article and a second article image of a second article. The first article image is integrated with the second article image, based on an article attribute to generate a transformed article image. The article attribute may be an attribute having a maximum likelihood of making the article popular. The transformed article image may be filtered based on predefined filtering rules to obtain a curated article design image. The curated article design image is assessed to generate a design score indicative of a popularity and/or a sellability of an article, and a design of the article may be selected for a post design selection process, based on the design score.Type: GrantFiled: December 23, 2019Date of Patent: May 3, 2022Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Nitish Bhardwaj, Sakshi Jain, Kumar Abhinav, Suma Mani Kuriakose, Veenu Arora, Alpana Dubey, Dhruv Bajpai
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Publication number: 20210256434Abstract: The disclosed system and method provide a way to create, update, and execute dynamic goal plans. Updating a dynamic goal plan may be based on the initial sequence of actions of the goal plan as well as the corresponding states of the actions. By using a sequence to sequence model, a goal plan can still be processed when the length of the input (initial sequence of actions) differs from the length of the output (updated sequence of actions). A sequence to sequence model can determine the interdependencies between actions that can contribute to the optimal order in which actions can efficiently be performed. A single layer neural network or clustering can be used to approximate the state of a goal plan that may be capable infinite states. This approximation improves accuracy in capturing the state of a goal plan, thereby improving accuracy in predicting the future state of a system, which can help with planning (e.g., gathering resources in advance).Type: ApplicationFiled: February 19, 2020Publication date: August 19, 2021Inventors: Alpana Dubey, Kumar Abhinav, Sakshi Jain, Veenu Arora
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Publication number: 20200257963Abstract: The present disclosure relates to a system, and method for computer-based recursive learning of artificial intelligence (AI) apprentice agents. The system includes a system circuitry in communication with a database and a memory. The system circuitry is configured to receive a new data-structure comprising one or more inputs and a goal, and convert, using a perception agent, the one or more inputs of the new data-structure into one or more input feature parameters of the new data-structure. The system circuitry is configured to obtain, using a reasoning agent, an action for the new data-structure, and determine, using an evaluation agent, whether the action for the new data-structure generates the goal of the new data-structure. When it is determined that the action generates the goal of the new data-structure, the system circuitry is further configured to store the new data-structure in the database.Type: ApplicationFiled: August 30, 2019Publication date: August 13, 2020Inventors: Kumar ABHINAV, Alpana DUBEY, Sakshi JAIN, Veenu ARORA, Hindnavis Vijaya SHARVANI
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Publication number: 20200202598Abstract: Examples of article designing are described herein. In an example, image data, margin data, and sales data corresponding to a plurality of articles may be obtained. The obtained data may be analyzed to identify a first article image of a first article and a second article image of a second article. The first article image is integrated with the second article image, based on an article attribute to generate a transformed article image. The article attribute may be an attribute having a maximum likelihood of making the article popular. The transformed article image may be filtered based on predefined filtering rules to obtain a curated article design image. The curated article design image is assessed to generate a design score indicative of a popularity and/or a sellability of an article, and a design of the article may be selected for a post design selection process, based on the design score.Type: ApplicationFiled: December 23, 2019Publication date: June 25, 2020Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITEDInventors: Nitish BHARDWAJ, Sakshi Jain, Kumar Abhinav, Suma Mani Kuriakose, Veenu Arora, Alpana Dubey, Dhruv Bajpai
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Patent number: 10326729Abstract: An intelligent social feed generator system leverages existing social platforms to generate context specific social feeds having enhanced messages that facilitate context specific user actions. The system implements technical features that analyze messages on existing social platforms to determine a message context and identify responsive user actions. The system generates enhanced messages allowing the user to take such action. The system also dynamically generates an enhanced social feed based on a particular usage context, where the social feed is formed of messages that match the usage context.Type: GrantFiled: December 2, 2015Date of Patent: June 18, 2019Assignee: Accenture Global Services LimitedInventors: Gurdeep Singh, Alex Kass, Upendra Chintala, Veenu Arora
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Publication number: 20160162471Abstract: An intelligent social feed generator system leverages existing social platforms to generate context specific social feeds having enhanced messages that facilitate context specific user actions. The system implements technical features that analyze messages on existing social platforms to determine a message context and identify responsive user actions. The system generates enhanced messages allowing the user to take such action. The system also dynamically generates an enhanced social feed based on a particular usage context, where the social feed is formed of messages that match the usage context.Type: ApplicationFiled: December 2, 2015Publication date: June 9, 2016Inventors: Gurdeep Virdi, Alex Kass, Upendra Chintala, Veenu Arora