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    Caching techniques for a database change stream
    104.
    发明授权
    Caching techniques for a database change stream 有权

    公开(公告)号：US11650985B2

    公开(公告)日：2023-05-16

    申请号：US17446197

    申请日：2021-08-27

    Applicant: salesforce.com, inc.

    Inventor： Benjamin Busjaeger ,  Michael Sgroi

    IPC: G06F16/2455 ,  G06F16/22 ,  G06F16/23

    CPC classification number: G06F16/24552 ,  G06F16/2282 ,  G06F16/2358 ,  G06F16/24568

    Abstract: Techniques are disclosed relating to caching techniques for processing a database change stream. A computer system may receive change records from a change stream that includes a plurality of records indicating changes to a database table. The change stream may include change records for multiple shards and be accessible by providing one or more position indicators for one or more of the multiple shards to request one or more change records and an updated position indicator. The system may store, for changes to a set of one or more shards, one or more cache entries that include respective groups of change records. The system may request a portion of the change stream by providing a received position indicator. The system may provide one or more cached change records from a cache entry that matches the provided position indicator.

    Continual neural network learning via explicit structure learning
    106.
    发明授权
    Continual neural network learning via explicit structure learning 有权

    公开(公告)号：US11645509B2

    公开(公告)日：2023-05-09

    申请号：US16176419

    申请日：2018-10-31

    Applicant: salesforce.com, inc.

    Inventor： Yingbo Zhou ,  Xilai Li ,  Caiming Xiong

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/08 ,  G06N3/04

    Abstract: Embodiments for training a neural network using sequential tasks are provided. A plurality of sequential tasks are received. For each task in the plurality of tasks a copy of the neural network that includes a plurality of layers is generated. From the copy of the neural network a task specific neural network is generated by performing an architectural search on the plurality of layers in the copy of the neural network. The architectural search identifies a plurality of candidate choices in the layers of the task specific neural network. Parameters in the task specific neural network that correspond to the plurality of candidate choices and that maximize architectural weights at each layer are identified. The parameters are retrained and merged with the neural network. The neural network trained on the plurality of sequential tasks is a trained neural network.

    SOFTWARE DEVELOPMENT TOOL AND SYSTEMS
    107.
    发明申请
    SOFTWARE DEVELOPMENT TOOL AND SYSTEMS 有权

    公开(公告)号：US20230133878A1

    公开(公告)日：2023-05-04

    申请号：US17513727

    申请日：2021-10-28

    Applicant: Salesforce.com, inc.

    Inventor： David KAYTES

    IPC: G06F8/34 ,  G06F8/10

    Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for implementing a software development tool that enables a set of computer-readable instructions to be requested and obtained in association with an element of a process flow represented in a layout. A set of specifications can be submitted in association with a request, where the set of specifications includes input-output value pairs. In response, the system can automatically generate a first set of computer-readable instructions according to the set of specifications, where the first set of computer-readable instructions implements a mapping between the input-output value pairs. In addition, the system can obtain a second set of computer-readable instructions according to the set of specifications, either from pre-existing software code or from individual(s) (e.g., software developer(s)) to whom the system has sent a request for computer-readable instructions. The system can replace the first set of computer-readable instructions with the second set of computer-readable instructions.

    One-to-Many Automatic Content Generation
    108.
    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 PRODUCT DESCRIPTION GENERATION
    109.
    发明申请
    AUTOMATIC PRODUCT DESCRIPTION GENERATION 有权

    公开(公告)号：US20230128686A1

    公开(公告)日：2023-04-27

    申请号：US17509024

    申请日：2021-10-24

    Applicant: salesforce.com, inc.

    Inventor： Michael Sollami ,  Xiangyu Peng

    IPC: G06K9/68 ,  G06K9/62 ,  G06K9/72

    Abstract: Systems, devices, and techniques are disclosed for automatic product description generation. A first set of features including labels including words may be generated from an image using a first feature extraction model. A second set of features including labels including words may be generated from the image using a second feature extraction model. A text description of a product depicted in the image may be generated by inputting the image and metadata for the image to a description generating model. The text description may include words. Each of the words may be generated by assigning probabilities to candidate words, boosting the assigned probabilities of candidate words that are similar to words of labels of the first set of features or words of labels of the second set of features, and selecting one of the candidate words based on the assigned probabilities after the boosting as a word of the text description.

    DYNAMIC ASSET MANAGEMENT SYSTEM AND METHODS FOR GENERATING INTERACTIVE SIMULATIONS REPRESENTING ASSETS BASED ON AUTOMATICALLY GENERATED ASSET RECORDS
    110.
    发明申请
    DYNAMIC ASSET MANAGEMENT SYSTEM AND METHODS FOR GENERATING INTERACTIVE SIMULATIONS REPRESENTING ASSETS BASED ON AUTOMATICALLY GENERATED ASSET RECORDS 有权

    公开(公告)号：US20230128293A1

    公开(公告)日：2023-04-27

    申请号：US18146007

    申请日：2022-12-23

    Applicant: salesforce.com, inc.

    Inventor： Charles Hart Isaacs

    IPC: G06F30/20 ,  G06F9/451 ,  G06F16/27

    Abstract: Methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. Based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. A simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. The user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.

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