Patents by Inventor Lionel Wolberger

Lionel Wolberger 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).

  • Machine learning systems and methods for automated prediction of innovative solutions to targeted problems
    Patent number: 11475330
    Abstract: A machine learning server is provided for predicting innovations in one or more scenarios. The machine learning server includes a processor and a memory in communication with the processor. The processor is configured to receive a user input, define a scenario profile based on the user input, apply a first trained machine learning model to the scenario profile to generate at least one target associated with the scenario, wherein the at least one target includes a measurable outcome, prompt for a user selection from the target, apply a second trained machine learning model to the scenario profile and the user selection from the at least one target to generate at least one candidate innovation predicted to achieve the measureable desired outcome, obtain descriptive information related to the at least one candidate innovation, and present the descriptive information related to the at least one candidate innovation.
    Type: Grant
    Filed: June 5, 2020
    Date of Patent: October 18, 2022
    Assignee: DMASS, INC.
    Inventors: Kathryn Lewis, Lionel Wolberger, Howard Brown
  • MACHINE LEARNING SYSTEMS AND METHODS FOR AUTOMATED PREDICTION OF INNOVATIVE SOLUTIONS TO TARGETED PROBLEMS
    Publication number: 20200387812
    Abstract: A machine learning server is provided for predicting innovations in one or more scenarios. The machine learning server includes a processor and a memory in communication with the processor. The processor is configured to receive a user input, define a scenario profile based on the user input, apply a first trained machine learning model to the scenario profile to generate at least one target associated with the scenario, wherein the at least one target includes a measurable outcome, prompt for a user selection from the target, apply a second trained machine learning model to the scenario profile and the user selection from the at least one target to generate at least one candidate innovation predicted to achieve the measureable desired outcome, obtain descriptive information related to the at least one candidate innovation, and present the descriptive information related to the at least one candidate innovation.
    Type: Application
    Filed: June 5, 2020
    Publication date: December 10, 2020
    Applicant: dMASS, Inc.
    Inventors: Kathryn Lewis, Lionel Wolberger, Howard Brown