Computing at the edge is important in remote settings, however, conventional hardware is not optimized for utilizing deep neural networks. The Google Edge TPU is an emerging hardware accelerator that is cost, power and speed efficient, and is available for prototyping and production purposes. Here, I review the Edge TPU platform, the tasks that have been accomplished using the Edge TPU, and which steps are necessary to deploy a model to the Edge TPU hardware. The Edge TPU is not only capable of tackling common computer vision tasks, but also surpasses other hardware accelerators, especially when the entire model can be deployed to the Edge TPU. Co-embedding the Edge TPU in cameras allows a seamless analysis of primary data. In summary, the Edge TPU is a maturing system that has proven its usability across multiple tasks.

翻译：边缘的计算机在远程环境中很重要,但是,常规硬件在利用深神经网络方面并不是最优化的。 Google Edge TPU是一个新兴的硬件加速器,成本、电力和速度高效,可用于原型和生产目的。这里,我审查边缘TPU平台,这是使用边缘TPU完成的任务,也是向边缘TPU硬件部署模型的必要步骤。边缘TPU不仅能够处理共同的计算机愿景任务,而且超越其他硬件加速器,特别是整个模型可以被部署到边缘TPU时。同时将边缘TPU安装在照相机中,可以对原始数据进行无缝分析。简言之,Edge TPU是一个成熟的系统,它证明可以跨越多个任务。