Patents by Inventor Julian SEIBEL

Julian SEIBEL 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: 20250238707
    Abstract: Example systems and methods described herein relate to the automated generation of sample expressions. Metadata is accessed for each of a plurality of applications. The metadata includes a functional description of each application. Prompt data is provided to a generative machine learning model. The prompt data includes the metadata for each of the plurality of applications and an instruction to generate, for each of the plurality of applications, a plurality of sample expressions corresponding to user input provided to a digital assistant to invoke an action related to the application. One or more responses that were generated by the generative machine learning model based on the prompt data are processed to obtain output data including the plurality of sample expressions for each of the plurality of applications in a structured format. The output data is used to configure the digital assistant.
    Type: Application
    Filed: January 22, 2024
    Publication date: July 24, 2025
    Inventors: Sebastian Schuetz, Julian Seibel, Manuel Mecke, Jonas Brand
  • Publication number: 20250199757
    Abstract: Example systems and methods described herein relate to a digital assistant service with automated function calling. Prompt data is provided to a generative machine learning model. The prompt data includes user input and function data. The user input is received via a user interface associated with a digital assistant. The function data identifies a plurality of functions. A response from the generative machine learning model includes a function identifier associated with a function from among the plurality of functions. In response to detecting that the response includes the function identifier, the function is invoked to obtain output data. The output data is caused to be presented in the user interface associated with the digital assistant.
    Type: Application
    Filed: December 13, 2023
    Publication date: June 19, 2025
    Inventors: Julian Seibel, Torben Krieger, Steffren Terheiden, Sebastian Schuetz
  • Publication number: 20240144039
    Abstract: Various embodiments for a continuous learning system are described herein. An embodiment operates by receiving a query from a user and identifying an unknown phrase in the query. User feedback regarding the unknown phrase is requested and received. A first pre-existing entity of a plurality of pre-existing entities that corresponds to the received user feedback is identified. A relationship between the first pre-existing entity and the unknown is added to the knowledgebase. The query is executed against the knowledgebase using the first pre-existing entity. A response, to the executed query, is provided to the user.
    Type: Application
    Filed: November 1, 2022
    Publication date: May 2, 2024
    Inventors: Julian SEIBEL, Steffen TERHEIDEN
  • Patent number: 11113476
    Abstract: Disclosed herein are system, method, and computer program product embodiments for training a machine learning model and using the machine learning model to determine an intent associated with an utterance. An embodiment operates by receiving an utterance, determining a first vector based on the received utterance, and determining a second vector based on the received utterance. A third vector is generated by concatenating the first vector and the second vector. The third vector is used to perform at least one of classifying, using a machine learning model, the utterance to determine the intent associated with the utterance or training the machine-learning model.
    Type: Grant
    Filed: June 12, 2019
    Date of Patent: September 7, 2021
    Assignee: SAP SE
    Inventor: Julian Seibel
  • Publication number: 20200394269
    Abstract: Disclosed herein are system, method, and computer program product embodiments for training a machine learning model and using the machine learning model to determine an intent associated with an utterance. An embodiment operates by receiving an utterance, determining a first vector based on the received utterance, and determining a second vector based on the received utterance. A third vector is generated by concatenating the first vector and the second vector. The third vector is used to perform at least one of classifying, using a machine learning model, the utterance to determine the intent associated with the utterance or training the machine-learning model.
    Type: Application
    Filed: June 12, 2019
    Publication date: December 17, 2020
    Inventor: Julian SEIBEL