Systems and Methods for Analysis of Internal Data Using Generative AI

    公开(公告)号:US20240289851A1

    公开(公告)日:2024-08-29

    申请号:US18196682

    申请日:2023-05-12

    CPC classification number: G06Q30/0282 G06F16/3329 G06Q30/0203

    Abstract: Systems and methods are described for identifying impactful elements in database information to generate a dialogue output. The method may include: (1) receiving, by one or more processors, internal database information at a generative artificial intelligence (AI) model, wherein the internal database information includes data associated with interaction dialogue; (2) analyzing, by the one or more processors, the internal database information via the generative AI model to generate an internal database analysis; (3) identifying, by the one or more processors and based upon at least the internal database analysis, one or more impact elements regarding human understanding of the internal database information via the generative AI model; and (4) generating, by the one or more processors and based upon at least the one or more impact elements, a dialogue output (or visual or virtual output) regarding the data via the generative AI model.

    Systems and Methods for Analysis of User Telematics Data Using Generative AI

    公开(公告)号:US20240289362A1

    公开(公告)日:2024-08-29

    申请号:US18196691

    申请日:2023-05-12

    CPC classification number: G06F16/3329 G06Q40/08 G06Q50/01

    Abstract: Systems and methods are described for analyzing user data to generate a dialogue output. The method may include: (1) receiving, by one or more processors, an indication of a user identity for a user at a generative artificial intelligence (AI) model; (2) retrieving, by the one or more processors and based upon at least the user identity, user data from one or more publicly accessible sources; (3) determining, by the one or more processors and based upon at least the user data, one or more personalization characteristics associated with at least an information retention rate for the user via the generative AI model; and (4) generating, by the one or more processors and based upon at least the one or more personalization characteristics, a personalized dialogue output (or visual or virtual output for display) for the user via the generative AI model.

    INSURANCE FOR METAVERSE ITEMS
    44.
    发明公开

    公开(公告)号:US20240104665A1

    公开(公告)日:2024-03-28

    申请号:US18124434

    申请日:2023-03-21

    CPC classification number: G06Q40/08

    Abstract: The following relates generally to providing insurance for one or more virtual items in a virtual environment. In some embodiments, an insurance server receives a request for insurance for one or more virtual items from a customer. The insurance server then obtains information associated with the one or more virtual items from a virtual environment server, and determines an insurance premium based upon the received information. The following also relates generally to providing backups of virtual items. In some embodiments, a backup server creates backups of virtual items by writing data associated with the virtual item to a data store. The virtual items may be fungible or non-fungible. In some embodiments, the virtual items are periodically backed up.

    Managing self-driving behavior of autonomous or semi-autonomous vehicle based upon actual driving behavior of driver

    公开(公告)号:US11623649B2

    公开(公告)日:2023-04-11

    申请号:US17848232

    申请日:2022-06-23

    Abstract: A system and method for measuring a driver's actual driving behaviors (e.g., acceleration, deceleration) in a manual driving mode to determine their preferred driving style, and then causing an autonomous or semi-autonomous vehicle to operate itself, within limits, in accordance with the drivers' driving style when operating in a self-driving mode, thereby providing a more familiar and comfortable driving experience for the driver. Data is collected on the actual driving behavior, any pre-existing data is accessed on the actual driving behavior, and the collected data and the pre-existing data are combined. A custom control is then created based upon the combined data, and the custom control is applied to manage the self-driving behavior of the autonomous or semi-autonomous vehicle in a self-driving mode. Additional data continues to be collected on the actual driving behavior, and the custom control is adjusted based upon the collected additional data.

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