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.
Cite
@article{arxiv.2212.03332,
title = {Edge Impulse: An MLOps Platform for Tiny Machine Learning},
author = {Shawn Hymel and Colby Banbury and Daniel Situnayake and Alex Elium and Carl Ward and Mat Kelcey and Mathijs Baaijens and Mateusz Majchrzycki and Jenny Plunkett and David Tischler and Alessandro Grande and Louis Moreau and Dmitry Maslov and Artie Beavis and Jan Jongboom and Vijay Janapa Reddi},
journal= {arXiv preprint arXiv:2212.03332},
year = {2023}
}