We are at the cusp of a new era in AI. Recently deep learning has revolutionised the field of Computer Vision, disrupting more traditional algorithmic approaches to object recognition, scene analysis and image understanding. But to date most of the applications of AI have relied on cloud-based services doing the heavy-lifting. Today we are at the cusp of a new era where AI data analysis is ready to move from the cloud and transition into the end device itself. In this talk we will review some of the Neural accelerators that are available today and look 1-2 years into the future to explore some of the potential impacts of edge-AI. We will also look at some of the new challenges and opportunities as AI migrates into individual devices: data-processing in the cloud won't go away, but more interestingly new computational & storage demands will emerge to support training of edge-AI. Among these will be the rise of 'Fake Data' and the VR tools and associated infrastructure required to scale the training of advanced Edge-AI solutions.