Edge Impulse：面向微型机器学习的MLOps平台
Edge Impulse: An MLOps Platform for Tiny Machine Learning
AI总结：
针对TinyML工作流软件栈碎片化、硬件异构导致模型优化难、移植性差的问题，本文提出基于云的MLOps平台Edge Impulse，通过多软硬件优化构建可扩展可移植软件栈以简化设计周期，截至2022年10月已承载超11万项目。
摘要：
Edge Impulse是一款基于云的机器学习运维（MLOps）平台，用于开发可部署到各类硬件目标的嵌入式与边缘机器学习（TinyML）系统。当前TinyML工作流受软件栈碎片化、部署硬件异构性困扰，导致ML模型优化难度大且可移植性差。我们推出Edge Impulse，这是一款可规模化开发TinyML系统的实用MLOps平台。该平台支持多种软硬件优化，为众多嵌入式系统构建可扩展、可移植的软件栈，从而解决上述挑战并简化TinyML设计周期。截至2022年10月，Edge Impulse已承载来自50953名开发者的118185个项目。
英文摘要：
Edge Impulse is a cloud-based machine learning operations (MLOps) platform for developing embedded and edge ML (TinyML) systems that can be deployed to a wide range of hardware targets. Current TinyML workflows are plagued by fragmented software stacks and heterogeneous deployment hardware, making ML model optimizations difficult and unportable. We present Edge Impulse, a practical MLOps platform for developing TinyML systems at scale. Edge Impulse addresses these challenges and streamlines the TinyML design cycle by supporting various software and hardware optimizations to create an extensible and portable software stack for a multitude of embedded systems. As of Oct. 2022, Edge Impulse hosts 118,185 projects from 50,953 developers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
