Patents by Inventor Sarah Lynch

Sarah Lynch 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).

  • Publication number: 20220128291
    Abstract: A system is described herein that includes a smart or an artificial intelligence (AI) refrigerator for use in retail, a server, and a computing device associated with a customer. The server utilizes one or more computer vision or artificial intelligence means to control the AI refrigerator.
    Type: Application
    Filed: October 7, 2021
    Publication date: April 28, 2022
    Applicant: Mama Gaia Smart Fridge Corporation dba Mama Gaia
    Inventors: Sarah Lynch, Giovanni Sudiro
  • Patent number: 11200452
    Abstract: A computer-implemented method according to one embodiment includes identifying a first classifier training data element and a second classifier training data element, calculating a similarity metric between the first classifier training data element and the second classifier training data element, and determining a classification for the first classifier training data element and the second classifier training data element, utilizing the similarity metric between the first classifier training data element and the second classifier training data element.
    Type: Grant
    Filed: January 30, 2018
    Date of Patent: December 14, 2021
    Assignee: International Business Machines Corporation
    Inventors: Stefan Van Der Stockt, Sihang B. Fang, Manali Jairam Chanchlani, Rahul P. Akolkar, Sarah Lynch, Kristi Farinelli
  • Patent number: 11003705
    Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to produce a physical action or transformation of a physical hardware device.
    Type: Grant
    Filed: February 26, 2018
    Date of Patent: May 11, 2021
    Assignee: International Business Machines Corporation
    Inventors: Stefan A. Van Der Stockt, Sihang B. Fang, Sarah Lynch, Joseph L. Sharpe, III, Rahul P. Akolkar, Brian E. Bissell, Manali J. Chanchlani
  • Patent number: 10740544
    Abstract: Embodiments provide a computer implemented method in a data processing system including a processor and memory storing instructions, which are executed by the processor to cause the processor to implement the method for providing an annotation policy for annotating a corpus including a plurality of electronic documents. The method includes: annotating an occurrence of a first term with a class in an electronic document; recommending a new annotation policy based on at least one annotation for the occurrence of first term; and storing the new annotation policy in a storage device.
    Type: Grant
    Filed: July 11, 2018
    Date of Patent: August 11, 2020
    Assignee: International Business Machines Corporation
    Inventors: Sarah Lynch, Kristi Farinelli, Rahul P. Akolkar, Alexander Block, Joseph L. Sharpe, III, Stefan Van Der Stockt
  • Patent number: 10565189
    Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.
    Type: Grant
    Filed: February 26, 2018
    Date of Patent: February 18, 2020
    Assignee: International Business Machines Corporation
    Inventors: Stefan A. Van Der Stockt, Sihang B. Fang, Sarah Lynch, Joseph L. Sharpe, III, Rahul P. Akolkar, Brian E. Bissell, Manali J. Chanchlani
  • Publication number: 20200019599
    Abstract: Embodiments provide a computer implemented method in a data processing system including a processor and memory storing instructions, which are executed by the processor to cause the processor to implement the method for providing an annotation policy for annotating a corpus including a plurality of electronic documents. The method includes: annotating an occurrence of a first term with a class in an electronic document; recommending a new annotation policy based on at least one annotation for the occurrence of first term; and storing the new annotation policy in a storage device.
    Type: Application
    Filed: July 11, 2018
    Publication date: January 16, 2020
    Inventors: Sarah Lynch, Kristi Farinelli, Rahul P. Akolkar, Alexander Block, Joseph L. Sharpe, III, Stefan Van Der Stockt
  • Publication number: 20190266281
    Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.
    Type: Application
    Filed: February 26, 2018
    Publication date: August 29, 2019
    Applicant: International Business Machines Corporation
    Inventors: Stefan A. Van Der Stockt, Sihang B. Fang, Sarah Lynch, Joseph L. Sharpe, III, Rahul P. Akolkar, Brian E. Bissell, Manali J. Chanchlani
  • Publication number: 20190266270
    Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.
    Type: Application
    Filed: February 26, 2018
    Publication date: August 29, 2019
    Applicant: International Business Machines Corporation
    Inventors: Stefan A. Van Der Stockt, Sihang B. Fang, Sarah Lynch, Joseph L. Sharpe, III, Rahul P. Akolkar, Brian E. Bissell, Manali J. Chanchlani
  • Publication number: 20190236409
    Abstract: A computer-implemented method according to one embodiment includes identifying a first classifier training data element and a second classifier training data element, calculating a similarity metric between the first classifier training data element and the second classifier training data element, and determining a classification for the first classifier training data element and the second classifier training data element, utilizing the similarity metric between the first classifier training data element and the second classifier training data element.
    Type: Application
    Filed: January 30, 2018
    Publication date: August 1, 2019
    Inventors: Stefan Van Der Stockt, Sihang B. Fang, Manali Jairam Chanchlani, Rahul P. Akolkar, Sarah Lynch, Kristi Farinelli