The majority of AI computing today is done in the cloud – mostly in the servers of Google Cloud, Amazon Web Services and Microsoft Azure.
The main problem with the Edge Computing development is that the current CPUs can handle only a certain level of computations. Advanced data processing and especially machine learning – both expected in today’s complex applications, are unattainable at the mere CPU level.
Furthermore, new edge computing products coupled with artificial intelligence algorithms require integration of high capacity processing together with AI accelerators, a time consuming and engineering-intensive feat.
Enablement of AI at the edge offers several advantages:
