GENERATING AND DEPLOYING PACKAGES FOR MACHINE LEARNING AT EDGE DEVICES

    公开(公告)号:US20190156246A1

    公开(公告)日:2019-05-23

    申请号:US15884279

    申请日:2018-01-30

    Abstract: A provider network implements a machine learning deployment service for generating and deploying packages to implement machine learning at connected devices. The service may receive from a client an indication of an inference application, a machine learning framework to be used by the inference application, a machine learning model to be used by the inference application, and an edge device to run the inference application. The service may then generate a package based on the inference application, the machine learning framework, the machine learning model, and a hardware platform of the edge device. To generate the package, the service may optimize the model based on the hardware platform of the edge device and/or the machine learning framework. The service may then deploy the package to the edge device. The edge device then installs the inference application and performs actions based on inference data generated by the machine learning model.

    DEVICE COMMUNICATION ENVIRONMENT
    42.
    发明申请

    公开(公告)号:US20190097989A1

    公开(公告)日:2019-03-28

    申请号:US16116719

    申请日:2018-08-29

    Abstract: A computing environment is disclosed that receives from devices requests directed toward services accessible in the environment, and that forwards communications from services in the environment to devices registered with the environment. During a registration process at the environment, devices are assigned a device identifier that is used to identify and authenticate each particular device and requests communicated from and to the device via the environment. The computing environment maintains state information for each device that has been registered with the system. As the device interacts with the system, the state information is updated to reflect the changes in the device. When requests to perform functions are received from devices, the computing environment determines for the particular device and the particular function requested what processing needs to be performed by the environment in response to the request.

    SPLIT PREDICTIONS FOR IOT DEVICES
    43.
    发明申请

    公开(公告)号:US20190037638A1

    公开(公告)日:2019-01-31

    申请号:US15660857

    申请日:2017-07-26

    Abstract: A hub device of a network receives data from edge devices and generates a local result. The hub device also sends the data to a remote provider network and receives a result from the remote provider network, wherein the result is based on the data received from the edge devices. The hub device then generates a response based on the local result or the received result. The hub device may determine to correct the local result based on the result received from the remote provider network, and generate the response based on the corrected result. The hub device may generate an initial response before receiving the result from the provider network. For example, the hub device may determine that the confidence level for the local result is above the threshold level and in response, generate the initial response based on the local result.

    TRAINING MODELS FOR IOT DEVICES
    44.
    发明申请

    公开(公告)号:US20190036716A1

    公开(公告)日:2019-01-31

    申请号:US15660859

    申请日:2017-07-26

    Abstract: A model training service of a provider network receives data from edge devices of a remote network. The model training service analyzes the received data. The model training service may also analyze global data from other edge devices of other remote networks. The model training service may then generate updates to local data processing models based on the analysis. The updates are configured to update the local data processing models at the edge devices of the remote network. The provider network deploys the updates to the remote network. The updates are then applied to the data processing models of the edge devices.

    Device gateway
    45.
    发明授权

    公开(公告)号:US10091329B2

    公开(公告)日:2018-10-02

    申请号:US14755959

    申请日:2015-06-30

    Abstract: A computing environment is disclosed that receives from devices requests directed toward services accessible in the environment, and that forwards communications from services in the environment to devices registered with the environment. During a registration process at the environment, devices are assigned a device identifier that is used to identify and authenticate each particular device and requests communicated from and to the device via the environment. The computing environment maintains state information for each device that has been registered with the system. As the device interacts with the system, the state information is updated to reflect the changes in the device. When requests to perform functions are received from devices, the computing environment determines for the particular device and the particular function requested what processing needs to be performed by the environment in response to the request.

    DEVICE GATEWAY
    46.
    发明申请
    DEVICE GATEWAY 审中-公开

    公开(公告)号:US20180227388A1

    公开(公告)日:2018-08-09

    申请号:US15886503

    申请日:2018-02-01

    CPC classification number: H04L67/327 H04L67/2823

    Abstract: A computing environment is disclosed that receives from devices requests directed toward services accessible in the environment, and that forwards communications from services in the environment to devices registered with the environment. During a registration process at the environment, devices are assigned a device identifier that is used to identify and authenticate each particular device and requests communicated from and to the device via the environment. The computing environment maintains state information for each device that has been registered with the system. As the device interacts with the system, the state information is updated to reflect the changes in the device. When requests to perform functions are received from devices, the computing environment determines for the particular device and the particular function requested what processing needs to be performed by the environment in response to the request.

    REMOTE INVOCATION OF CODE EXECUTION IN A LOCALIZED DEVICE COORDINATOR

    公开(公告)号:US20180150341A1

    公开(公告)日:2018-05-31

    申请号:US15362707

    申请日:2016-11-28

    Abstract: Systems and methods are described for implementing a coordinator within a coordinated environment, which environment includes set of coordinated devices managed by the coordinator. The coordinator can be provisioned with a set of tasks, each task corresponding to a segment of code that can be executed by the coordinator, such as to manage the coordinated devices. To assist in execution of the tasks, the coordinator can include a remote interface that enables retrieval of task calls from an external system, such as an external on-demand code execution environment. The remote interface may periodically retrieve calls from the external system, and generate corresponding call messages on the coordinator to cause executions of called tasks. The remote interface can further obtain outputs of such executions, and report those outputs to the external system.

    Local data classification based on a remote service interface

    公开(公告)号:US12045264B2

    公开(公告)日:2024-07-23

    申请号:US18055324

    申请日:2022-11-14

    CPC classification number: G06F16/285 G06F3/0604 G06F18/24 G06N20/00

    Abstract: A connected device at a client network implements a local data classification service for classifying data based on a data classification service of a remote provider network. The local data classification service receives a request to classify data at one or more data sources of the client network. The request is initiated from a client device of the client network according to a management interface for a data classification service of a remote provider network (e.g., using the same API request used by the remote classification service). The local data classification service obtains at least some of the data from the one or more data sources of the client network. The local data classification service classifies the obtained data according to different types of sensitivity using the data classification engine in the execution environment without the data being exposed outside of a data isolation boundary of the client network.

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