Back in 2016, Google revealed their custom built Tensor Processing Unit chips that were explicitly designed for machine learning tasks, and just last year, they started renting out cloud-based access to updated versions of that AI hardware. These monster ASICs are squarely aimed at ML training tasks, but during that same period, Google also released a small, low power Edge TPU designed to run algorithms the big chips train a little closer to home. Previously, these "Edge" ML chips were only available to rent through Google, but, an Alphabet spin-off called Coral just started selling the Edge TPUs through Mouser. Interested parties can buy self-contained development boards complete with an ARM CPU, an integrated GPU, I/O, and Ethernet for $149, while a USB accessory akin to an Intel Compute Stick will set you back $75. A PCI-E based accelerator and a 40mm x 40mm "System on Module" are said to be coming sometime in 2019, but there's no word on when, or if, Google will ever sell the bigger TPU ASICs as discrete co-processors. AI is pervasive today, from consumer to enterprise applications. With the explosive growth of connected devices, combined with a demand for privacy/confidentiality, low latency and bandwidth constraints, AI models trained in the cloud increasingly need to be run at the edge. Edge TPU is Google's purpose-built ASIC designed to run AI at the edge. It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge.