NOTIFICATION OF CHANGE OF VALUE IN STALE CONTENT

    公开(公告)号:US20220350847A1

    公开(公告)日:2022-11-03

    申请号:US17806979

    申请日:2022-06-15

    Applicant: GOOGLE LLC

    Abstract: A method can include determining that a tab is stale, determining a first universal resource locator (URL) associated with the tab, determining that content presented by the stale tab corresponds to an object that is also presented by content associated with a second URL, determining, based on content associated with at least one of the first URL or the second URL, that a value of an attribute associated with the object has changed from the value of the attribute when the tab presented the object, and outputting a notification that the value of the attribute associated with the object has changed.

    Notification of change of value in stale content

    公开(公告)号:US11366868B1

    公开(公告)日:2022-06-21

    申请号:US17249763

    申请日:2021-03-11

    Applicant: GOOGLE LLC

    Abstract: A method can include determining that a tab is stale, determining a first universal resource locator (URL) associated with the tab, determining that content presented by the stale tab corresponds to an object that is also presented by content associated with a second URL, determining, based on content associated with at least one of the first URL or the second URL, that a value of an attribute associated with the object has changed from the value of the attribute when the tab presented the object, and outputting a notification that the value of the attribute associated with the object has changed.

    Machine-Learned Model System
    4.
    发明申请

    公开(公告)号:US20200151611A1

    公开(公告)日:2020-05-14

    申请号:US16617333

    申请日:2018-05-25

    Applicant: Google LLC

    Abstract: Provided are methods, systems, devices, and tangible non-transitory computer readable media for providing data associated with a machine-learned model library. The disclosed technology can perform operations including providing a machine-learned GP model library that includes a plurality of machine-learned models trained to generate semantic observations based on sensor data associated with a vehicle. Each machine-learned model of the plurality of machine-learned models can be associated with one or more configurations supported by each machine-learned model. A request for a machine-learned model from the machine-learned model library can be received a remote computing device. Furthermore, based on the request, the machine-learned model can be provided to the remote computing device.

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