�ݺ�ߣshows by User: doyu

�ݺ�ߣshows by User: doyu / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: doyu / Sat, 29 Jan 2022 06:17:18 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: doyu TinyML as-a-Service ecosystem for ML in IoT /slideshow/tinyml-asaservice-ecosystem-for-ml-in-iot/251075546 1621985531132-220129061718
Tiny Machine Learning (TinyML) is an emerging concept that concerns the execution of ML tasks on very constrained IoT devices. Although TinyML has generated a strong R&D interest around it, various challenges limit its effective execution in the constrained devices world, with the result of slowing down the development of a complete ecosystem around it. TinyML as-a-Service (TinyMLaaS) aims to fill the gap in this respect, with the definition of a set of guidelines that can enable an easier democratization of TinyML. In this paper, we describe how the "as-a-Service" model is bound to TinyML, by providing an overview of our concept and introducing the design requirements and building blocks that can make TinyMLaaS reality.]]>
Tiny Machine Learning (TinyML) is an emerging concept that concerns the execution of ML tasks on very constrained IoT devices. Although TinyML has generated a strong R&D interest around it, various challenges limit its effective execution in the constrained devices world, with the result of slowing down the development of a complete ecosystem around it. TinyML as-a-Service (TinyMLaaS) aims to fill the gap in this respect, with the definition of a set of guidelines that can enable an easier democratization of TinyML. In this paper, we describe how the "as-a-Service" model is bound to TinyML, by providing an overview of our concept and introducing the design requirements and building blocks that can make TinyMLaaS reality.]]> Sat, 29 Jan 2022 06:17:18 GMT /slideshow/tinyml-asaservice-ecosystem-for-ml-in-iot/251075546 doyu@slideshare.net(doyu) TinyML as-a-Service ecosystem for ML in IoT doyu Tiny Machine Learning (TinyML) is an emerging concept that concerns the execution of ML tasks on very constrained IoT devices. Although TinyML has generated a strong R&D interest around it, various challenges limit its effective execution in the constrained devices world, with the result of slowing down the development of a complete ecosystem around it. TinyML as-a-Service (TinyMLaaS) aims to fill the gap in this respect, with the definition of a set of guidelines that can enable an easier democratization of TinyML. In this paper, we describe how the "as-a-Service" model is bound to TinyML, by providing an overview of our concept and introducing the design requirements and building blocks that can make TinyMLaaS reality. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/1621985531132-220129061718-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Tiny Machine Learning (TinyML) is an emerging concept that concerns the execution of ML tasks on very constrained IoT devices. Although TinyML has generated a strong R&D interest around it, various challenges limit its effective execution in the constrained devices world, with the result of slowing down the development of a complete ecosystem around it. TinyML as-a-Service (TinyMLaaS) aims to fill the gap in this respect, with the definition of a set of guidelines that can enable an easier democratization of TinyML. In this paper, we describe how the "as-a-Service" model is bound to TinyML, by providing an overview of our concept and introducing the design requirements and building blocks that can make TinyMLaaS reality.

TinyML as-a-Service ecosystem for ML in IoT from Hiroshi Doyu

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0 TinyML as-a-Service /slideshow/tinyml-asaservice/186862177 elc2019-tinymlaas-191025170009
ML on microcontroller with Unikernel]]>
ML on microcontroller with Unikernel]]> Fri, 25 Oct 2019 17:00:09 GMT /slideshow/tinyml-asaservice/186862177 doyu@slideshare.net(doyu) TinyML as-a-Service doyu ML on microcontroller with Unikernel <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/elc2019-tinymlaas-191025170009-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> ML on microcontroller with Unikernel

TinyML as-a-Service from Hiroshi Doyu

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0 MeeGo Architecture /slideshow/meego-architecture/6983755 e-4-110219082203-phpapp02
My talk at MeeGo Summer Seminar Tokyo 2010]]>
My talk at MeeGo Summer Seminar Tokyo 2010]]> Sat, 19 Feb 2011 08:21:55 GMT /slideshow/meego-architecture/6983755 doyu@slideshare.net(doyu) MeeGo Architecture doyu My talk at MeeGo Summer Seminar Tokyo 2010 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/e-4-110219082203-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> My talk at MeeGo Summer Seminar Tokyo 2010

MeeGo Architecture from Hiroshi Doyu

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0 Improving MeeGo boot-up time /slideshow/improving-meegobootuptime/5382526 improving-meego-boot-up-time-101007061957-phpapp01
My talk at LinuxCon Japan 2010.]]>
My talk at LinuxCon Japan 2010.]]> Thu, 07 Oct 2010 06:18:06 GMT /slideshow/improving-meegobootuptime/5382526 doyu@slideshare.net(doyu) Improving MeeGo boot-up time doyu My talk at LinuxCon Japan 2010. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/improving-meego-boot-up-time-101007061957-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> My talk at LinuxCon Japan 2010.

Improving MeeGo boot-up time from Hiroshi Doyu

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0 https://cdn.slidesharecdn.com/profile-photo-doyu-48x48.jpg?cb=1740305439 Kernel Engineer hiroshidoyu.emurse.com https://cdn.slidesharecdn.com/ss_thumbnails/1621985531132-220129061718-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/tinyml-asaservice-ecosystem-for-ml-in-iot/251075546 TinyML as-a-Service ec... https://cdn.slidesharecdn.com/ss_thumbnails/elc2019-tinymlaas-191025170009-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/tinyml-asaservice/186862177 TinyML as-a-Service https://cdn.slidesharecdn.com/ss_thumbnails/e-4-110219082203-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/meego-architecture/6983755 MeeGo Architecture