Machine Learning Process Detection
    2.
    发明公开

    公开(公告)号:US20240281528A1

    公开(公告)日:2024-08-22

    申请号:US18571153

    申请日:2021-07-23

    CPC classification number: G06F21/554

    Abstract: In some examples, the disclosure describes a device, comprising: a processor resource, and a non-transitory memory resource storing machine-readable instructions stored thereon that, when executed, cause the processor resource to generate a machine learning dataset, train and deploy a classifier using the machine learning dataset to determine whether a machine learning training process is running on a first computing device and whether the machine learning training process is malicious or is not malicious, and send an alert to the first computing device based on results of the trained classifier deployment on the first computing device.

    DEVICE SUITABILITY DETERMINATIONS
    3.
    发明公开

    公开(公告)号:US20230289272A1

    公开(公告)日:2023-09-14

    申请号:US17689736

    申请日:2022-03-08

    CPC classification number: G06F11/3058 G06F11/3438 G06N3/02

    Abstract: In an example in accordance with the present disclosure, a computing device is described. The computing device includes a database with a thermal dataset acquired during usage of a device. The computing device also includes a processor which trains a neural network to determine suitability of the device for a user of the device based on the thermal dataset. The neural network includes 1) an encoder trained to transform the thermal dataset to a first embedding vector, 2) a compression/decompression component trained to generate a second embedding vector that minimizes a difference from the thermal dataset based on the first embedding vector, and 3) a decoder trained to generate a second thermal dataset from the second embedding vector.

    DETECT AND PREVENT BATTERY SWELLING
    4.
    发明公开

    公开(公告)号:US20230408585A1

    公开(公告)日:2023-12-21

    申请号:US18250967

    申请日:2020-10-30

    CPC classification number: G01R31/371 G01R31/382

    Abstract: Examples are described herein for monitoring power source usage of a computing device, including a battery and another power source, over time. In various examples, time periods of this monitored time may be added to a time count based on their immediately previous or immediately subsequent time periods satisfying a condition. The time count may be used to track periods of time during which certain power source usage factors are present that may lead to or may indicate the presence of battery swelling. After a time period is added to the time count, the updated time count can be compared to a time count threshold, and a user of the computing device may be warned based on the comparison. The threshold and warning may be selected to warn a user of potential present or future swelling of the battery.

    COMPARISONS OF KNOWLEDGE GRAPHS REPRESENTING COMPUTER SYSTEMS

    公开(公告)号:US20220147839A1

    公开(公告)日:2022-05-12

    申请号:US17418548

    申请日:2019-07-15

    Abstract: An example of a non-transitory computer-readable medium to store machine-readable instructions to be executed by a processor. The instructions may cause the processor to create a first knowledge graph to represent a computer system at a first time. The first knowledge graph may include a first set of entries to represent a first set of components of the computer system. The instructions may cause the processor to create a second knowledge graph to represent the computer system at a second time after the first time. The instructions may cause the processor to compare the second knowledge graph with the first knowledge graph and perform a corrective action based on the comparison.

    SUPPLIER SELECTION
    10.
    发明申请
    SUPPLIER SELECTION 审中-公开

    公开(公告)号:US20200272960A1

    公开(公告)日:2020-08-27

    申请号:US16481800

    申请日:2017-11-17

    Abstract: A system may comprise a database to collect telemetry data corresponding to a particular component of a device. The system may further comprise a controller coupled to the database. The controller may receive telemetry data for the particular component from the database. The controller may further determine a plurality of metrics for the particular component based on the telemetry data, wherein the plurality of metrics is determined for a plurality of suppliers and select a particular supplier of the plurality of suppliers based on the determined plurality of metrics.

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