TinyML as a Service and machine learning at the edge – Ericsson
The TinyML as-a-Service project at Ericsson Research sets out to address the challenges that today limit the potential of machine learning (ML) paradigms at the edge of the embedded IoT world. In this post, the second post in our TinyML series, we take a closer look at the technical and non-technical challenges on our journey to making that happen. Learn more below.
This is the second post in a series about tiny machine learning (TinyML) at the deep IoT edge. Read our earlier introduction to TinyMl as-a-Service, to learn how it ranks in respect to traditional cloud-based machine learning or the embedded systems domain.