Configurable machine learning assemblies for autonomous operation in personal devices

    公开(公告)号:US20180025268A1

    公开(公告)日:2018-01-25

    申请号:US15396267

    申请日:2016-12-30

    CPC classification number: G06N3/063

    Abstract: Configurable machine learning assemblies for autonomous operation in personal devices are provided. Example systems implement machine learning based on neural networks that draw low power for use in smart phones, watches, drones, automobiles, and medical devices. The onboard machine learning assemblies can be powered by batteries, and once onboard a small personal device, can learn to perform object recognition and autonomous decision-making without access to outside resources. The assemblies can be small or even nano-scale, and may draw less than one watt of power on average. An assembly can be configured from pluggable, interchangeable modules that have compatible ports for interconnecting and integrating functionally dissimilar sensor systems. A core module contains a machine learning kernel, and multiple cores can be connected together to expand the neural network. An example machine learning assembly auto-detects sensors and peripherals, and extends a network or bus to all connected components.

Patent Agency Ranking