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    Per component schedulers making global scheduling decision
    1.
    发明授权
    Per component schedulers making global scheduling decision 有权

    公开(公告)号：US11475921B1

    公开(公告)日：2022-10-18

    申请号：US16996607

    申请日：2020-08-18

    Applicant: Amazon Technologies, Inc.

    Inventor： Gowtham Jeyabalan ,  Shubham Chandra Gupta ,  Jonathan Hedley ,  Nitin Singhal ,  Mark Hawley Yang ,  Jiazhi Ou

    IPC: G11B27/06 ,  G11B27/10 ,  G06F9/48 ,  G06N20/00 ,  G06N5/04 ,  G06F9/54 ,  G06V20/40

    Abstract: Techniques for analyzing stored video upon a request are described. For example, a method of receiving a first application programming interface (API) request to analyze a stored video, the API request to include a location of the stored video and at least one analysis action to perform on the stored video; scheduling a job for the first API request using a global scheduler, the global scheduler to schedule, based at least in part on available bandwidth of processing components including a segmenter, a chunk processor, and a reducer, at least one job queue associated at least one of the processing components; accessing the location of the stored video to retrieve the stored video; segmenting the accessed video into chunks; processing each chunk with a chunk processor to perform the at least one analysis action, each chunk processor to utilize at least one machine learning model in performing the at least one analysis action; joining the results of the processing of each chunk to generate a final result; storing the final result; and providing the final result to a requestor in response to a second API request is described.

    Distributed system for efficient entity recognition
    3.
    发明授权
    Distributed system for efficient entity recognition 有权

    公开(公告)号：US12039770B1

    公开(公告)日：2024-07-16

    申请号：US17219715

    申请日：2021-03-31

    Applicant: Amazon Technologies, Inc.

    Inventor： Aakash Deep ,  Jia Bi Zhang ,  Jonathan Hedley

    IPC: G06V10/75 ,  G06F18/22 ,  H04L67/10

    CPC classification number: G06V10/75 ,  G06F18/22 ,  H04L67/10

    Abstract: A first encoding representing a set of detected signals is obtained at a sensor-proximity resource of an object recognition application which also includes resources of an analytics service of a provider network. In response to a determination that a cache at the sensor-proximity resource does not include a second encoding which satisfies a similarity criterion with respect to the first encoding, at least a portion of a partition of a spatial index is obtained from another resource selected using an index partition map. A recognition-based action is initiated based on determining that the partition includes an encoding which satisfies the similarity criterion.

    DISTRIBUTED SYSTEM FOR EFFICIENT ENTITY RECOGNITION
    5.
    发明公开
    DISTRIBUTED SYSTEM FOR EFFICIENT ENTITY RECOGNITION 审中-公开

    公开(公告)号：US20240320951A1

    公开(公告)日：2024-09-26

    申请号：US18732243

    申请日：2024-06-03

    Applicant: Amazon Technologies, Inc.

    Inventor： Aakash Deep ,  Jia Bi Zhang ,  Jonathan Hedley

    IPC: G06V10/75 ,  G06F18/22 ,  H04L67/10

    CPC classification number: G06V10/75 ,  G06F18/22 ,  H04L67/10

    Abstract: A first encoding representing a set of detected signals is obtained at a sensor-proximity resource of an object recognition application which also includes resources of an analytics service of a provider network. In response to a determination that a cache at the sensor-proximity resource does not include a second encoding which satisfies a similarity criterion with respect to the first encoding, at least a portion of a partition of a spatial index is obtained from another resource selected using an index partition map. A recognition-based action is initiated based on determining that the partition includes an encoding which satisfies the similarity criterion.

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