  The use of Deep Learning and Machine Learning is becoming pervasive day by
day which is opening doors to new opportunities in every aspect of technology.
Its application Ranges from Health-care to Self-driving Cars, Home Automation
to Smart-agriculture, and Industry 4.0. Traditionally the majority of the
processing for IoT applications is being done on a central cloud but that has
its issues; which include latency, security, bandwidth, and privacy, etc. It is
estimated that there will be around 20 Million IoT devices by 2020 which will
increase problems with sending data to the cloud and doing the processing
there. A new trend of processing the data on the edge of the network is
emerging. The idea is to do processing as near the point of data production as
possible. Doing processing on the nodes generating the data is called Edge
Computing and doing processing on a layer between the cloud and the point of
data production is called Fog computing. There are no standard definitions for
any of these, hence they are usually used interchangeably. In this paper, we
have reviewed the development boards available for running Artificial
Intelligence algorithms on the Edge
