Selective simulation of virtualized hardware inputs

    公开(公告)号:US10740511B2

    公开(公告)日:2020-08-11

    申请号:US16394069

    申请日:2019-04-25

    Applicant: Google LLC

    Abstract: Methods and apparatus are described herein emulating, by one or more servers on behalf of a mobile computing device, a cloud-based virtual machine. The cloud-based virtual machine may include a virtualized hardware component that provides, as virtual hardware input for a software application executing on the cloud-based virtual machine, either “genuine” virtual hardware input or “simulated” virtual hardware input. Genuine virtual hardware input may be based on an actual hardware signal received from a hardware component of the mobile computing device that corresponds to the virtualized hardware component. Simulated virtual hardware input may be generated independently of any hardware signal associated with the hardware component. Output of the software application may be interactively streamed to the mobile computing device.

    Multi-layer test suite generation
    42.
    发明授权

    公开(公告)号:US10482002B2

    公开(公告)日:2019-11-19

    申请号:US16137038

    申请日:2018-09-20

    Applicant: Google LLC

    Abstract: A system and method for developing a multi-layered test suite for an operating platform including a framework layer and a system layer includes executing a first test suite against a version of the operating platform modified based on a software faults. A first counter is incremented if a first test suite executed against the modified version of the operating platform fails. A second test suite can be executed against the modified version of the operating platform and test cases may be added to the first test suite based on whether the second test suite passes or fails.

    OPERATING SYSTEM VALIDATION
    43.
    发明申请

    公开(公告)号:US20180336124A1

    公开(公告)日:2018-11-22

    申请号:US15840484

    申请日:2017-12-13

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for validating an operating system are disclosed. In one aspect, a method includes the actions of providing, to a computing device running an operating system that includes, a framework layer, a hardware abstraction layer, and a kernel that includes firmware and drivers, a reference system image that is configured to replace, supplement, or modify the framework layer. The actions further include providing, to the computing device, test data that is configured to verify functionality of the operating system by interacting with the reference system image to test functionality of the hardware abstraction layer without modifying the hardware abstraction layer, wherein the computing device with the framework layer replaced, supplemented, or modified by the reference system image is a non-rooted device. The actions further include determining whether the operating system of the computing device is functioning properly.

    Personalized Model Training for Users Using Data Labels

    公开(公告)号:US20250139448A1

    公开(公告)日:2025-05-01

    申请号:US18499621

    申请日:2023-11-01

    Applicant: Google LLC

    Inventor: Keun Soo Yim

    Abstract: Systems and methods for generating a machine-learned model are disclosed herein. The method can include receiving, by a computing system comprising one or more processors, one or more data items, the one or more data items being associated with usage of a user device by a user and inferring, by the one or more processors, one or more data labels based on the one or more data items, the data labels being indicative of the usage of the user device by the user. The method can also include generating, by the one or more processors, a personalized model using the one or more data labels and a base model.

    METHOD AND SYSTEM FOR UNDERSTANDING AND FULFILLING VERB-BASED SUCCINCT QUERIES

    公开(公告)号:US20250103648A1

    公开(公告)日:2025-03-27

    申请号:US18373192

    申请日:2023-09-26

    Applicant: Google LLC

    Abstract: Some implementations receive audio data capturing a verb-based succinct query that includes an action but is void of any app entity and determine, based on processing of the audio data, the action and one or more instance candidates associated with the action. Some of those implementations further query an app entity database for usage information and/or capability information of one or more app entities that correspond to the one or more instance candidates and generate, based on selecting from the one or more app entities, a response or action responsive to the verb-based succinct query.

    Encoding/decoding user interface interactions

    公开(公告)号:US12236064B2

    公开(公告)日:2025-02-25

    申请号:US18347374

    申请日:2023-07-05

    Applicant: Google LLC

    Abstract: A method of encoding and decoding user interface interactions includes receiving a query from a user captured by an assistant-enabled device associated with the user. The query includes a user intent for interacting with an application. The method includes obtaining, for the application, a set of categorized actions. Each categorized action of the set of categorized actions is associated with one or more parameters and represents a high-level description of the user intent of the user interacting with the application. For each respective categorized action of the set of categorized actions, the method includes selecting a respective script associated with the respective categorized action that performs one or more low-level interactions with the application and executing the respective script to represent the user intent for interacting with the application.

    Fulfillment of actionable requests ahead of a user selecting a particular autocomplete suggestion for completing a current user input

    公开(公告)号:US12223266B2

    公开(公告)日:2025-02-11

    申请号:US18377648

    申请日:2023-10-06

    Applicant: GOOGLE LLC

    Inventor: Keun Soo Yim

    Abstract: Implementations set forth herein relate to providing selectable autofill suggestions, which correspond to application actions that are at least partially fulfilled using server command data—prior to a user selecting a particular selectable autofill suggestion. Proactively fulfilling command data in this way mitigates latency between user selection of a suggestion and fulfillment of a particular action. Initially, a partial input can be processed to generate autofill suggestions, which can be communicated to a server device for further processing. The autofill suggestions can also be rendered for selection at a touch display interface, thereby allowing a user to select one of the autofill suggestions. As command fulfillment data is provided by the server, the command fulfillment data can be available to a corresponding application(s) in order that any corresponding actions can be at least partially fulfilled prior to user selection.

    Filtering third-party content related to applications based on installation status

    公开(公告)号:US20250004737A1

    公开(公告)日:2025-01-02

    申请号:US18276790

    申请日:2022-11-01

    Applicant: Google LLC

    Inventor: Keun Soo Yim

    Abstract: Techniques for filtering third-party content that is to be provided via a mobile computing device based on which applications are already installed on that mobile computing device are provided. An example method includes determining, by a server, a set of candidate mobile applications, including first and second applications, each associated with respective third-party content presentable on a mobile computing device; in response to determining that the first application is absent from a set of applications installed on the mobile computing device: sending, by the server to the mobile computing device, third-party content associated with the first application; and in response to determining that the second application is included in the set of applications installed on the mobile computing device: refraining from sending third-party content associated with the second application to the mobile computing device.

    RENDERING SUGGESTION FOR SEARCHING ENTITY WITHIN APPLICATION IN RESPONSE TO DETERMINING THE ENTITY IS ASSOCIATED WITH THE APPLICATION

    公开(公告)号:US20240411770A1

    公开(公告)日:2024-12-12

    申请号:US18390874

    申请日:2023-12-20

    Applicant: GOOGLE LLC

    Inventor: Keun Soo Yim

    Abstract: Implementations include recognizing entities in a user query received from a client device and determining whether any of the recognized entities is a personal entity using an entity database storing personal entities donated by applications installed at the client device. Application(s) or application action(s) can be determined based on entity information of the recognized entities, and suggestions can be generated to suggest the determined application(s) (or the determined application action(s)). For an application (or application action) determined based on a recognized entity that is determined as a personal entity, a suggestion for the application (or application action) can be boosted for display to a user of the client device.

    AUTOMATED ASSISTANT ARCHITECTURE FOR PRESERVING PRIVACY OF APPLICATION CONTENT

    公开(公告)号:US20240406128A1

    公开(公告)日:2024-12-05

    申请号:US18800656

    申请日:2024-08-12

    Applicant: GOOGLE LLC

    Inventor: Keun Soo Yim

    Abstract: Implementations set forth herein relate to an automated assistant that allows third party applications to inject dependencies to leverage automated assistant functions. Furthermore, enabling such dependency injections can allow third party applications to preserve privacy of any application content that is used during execution of automated assistant functions. In some implementations, a third party application can initialize a function with an assistant dependency using parameters that are tagged as private. Initializing a function in such as a way can allow private content communicated between the third party application and the automated assistant to be abstracted for security purposes. The abstracted content can thereafter be communicated to a remote server—such as a server hosting an extensively trained machine learning model. Intelligent output provided by the server can then be incorporated into one or more processes of the third party application without comprising security.

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