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    LEARNING AFFINITIES THROUGH DESIGN VARIATIONS
    4.
    发明申请
    LEARNING AFFINITIES THROUGH DESIGN VARIATIONS 有权

    公开(公告)号：US20210149961A1

    公开(公告)日：2021-05-20

    申请号：US17096830

    申请日：2020-11-12

    Applicant: salesforce.com, inc.

    Inventor： Brian J. Lonsdorf ,  Jessica Lundin ,  Owen Winne Schoppe ,  Sönke Rohde ,  Alan Ross ,  David James Woodward

    IPC: G06F16/9035 ,  G06F16/9038 ,  G06F16/904

    Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a user-preferred attribute type. An embodiment operates by maintaining user-presented attributes associated with user-presented records, wherein the user-presented attributes comprise one or more user-presented attribute types. After receiving a user-desired attribute of the user-presented attributes, a user-preferred attribute type of the user-presented attribute types is determined based on the user-presented attributes and the user-desired attribute. Thereafter, a new record and associated attribute are to be presented with the new attribute being of the user-preferred type.

    One-to-Many Automatic Content Generation
    6.
    发明申请
    One-to-Many Automatic Content Generation 有权

    公开(公告)号：US20230129431A1

    公开(公告)日：2023-04-27

    申请号：US17649016

    申请日：2022-01-26

    Applicant: salesforce.com, inc.

    Inventor： Michael Sollami ,  Sönke Rohde ,  Alan Martin Ross ,  David James Woodward ,  Jessica Lundin ,  Owen Winne Schoppe ,  Brian J. Lonsdorf ,  Aashish Jain

    IPC: G06F3/04845 ,  G06N3/04 ,  G06V10/771 ,  G06V10/762 ,  G06V10/82

    Abstract: Techniques are disclosed for automatically generating new content using a trained 1-to-N generative adversarial network (GAN) model. In disclosed techniques, a computer system receives, from a computing device, a request for newly-generated content, where the request includes current content. The computer system automatically generates, using the trained 1-to-N GAN model, N different versions of new content, where a given version of new content is automatically generated based on the current content and one of N different style codes, where the value of N is at least two. After generating the N different versions of new content, the computer system transmits them to the computing device. The disclosed techniques may advantageously automate a content generation process, thereby saving time and computing resources via execution of the 1-to-N GAN machine learning model.

    Automatic user interface data generation
    10.
    发明授权
    Automatic user interface data generation 有权

    公开(公告)号：US11379189B1

    公开(公告)日：2022-07-05

    申请号：US17354439

    申请日：2021-06-22

    Applicant: salesforce.com, inc.

    Inventor： Owen Winne Schoppe ,  Sönke Rohde ,  Brian J. Lonsdorf ,  Jessica Lundin ,  David J. Woodward ,  Alan Martin Ross ,  Michael Sollami

    IPC: G06F8/20 ,  G06F8/38 ,  G06N20/00 ,  G06F9/451

    Abstract: Techniques are disclosed relating to automatically synthesizing user interface (UI) component instances. In disclosed techniques a computer system receives a set of existing UI elements and a set of design rules for the set of existing elements, where design rules in the set of design rules indicate one or more allowed states for respective UI elements in the set of existing UI elements. The one or more allowed states may correspond to one or more visual characteristics. Using the set of existing UI elements, the computer system may then automatically generate a plurality of UI component instances based on the set of design rules, where a respective UI component instance includes a first UI element in a first allowed state. The computer system may then train, using the plurality of UI component instances, a machine learning model operable to automatically generate UI designs.

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