This report was 1st published on our sister Site, The Internet Of All Things.
Google has announced two products “aimed at helping customers develop and deploy intelligent connected devices at scale” – Edge TPU, a hardware chip, and Cloud IoT Edge, a software stack that extends Google Cloud’s powerful AI capability to gateways and connected devices.
Google said on its official blog that the new products will let companies build and train ML models in the Cloud, then run those models on the Cloud IoT Edge device through the power of the Edge TPU hardware accelerator.
Edge TPU is Google’s purpose-built ASIC chip designed to run TensorFlow Lite ML models at the edge. The design of Edge TPU is such it focuses on optimizing for “performance per watt” and “performance per dollar” within a small footprint.
Edge TPUs are designed to complement the Cloud TPU offering, to accelerate ML training in the Cloud, then have lightning-fast ML inference at the edge. Sensors running them, said Google, will become more than data collectors—they make local, real-time, intelligent decisions.
The Edge TPU chip, shown with a standard U.S. penny for reference
Cloud IoT Edge is the software that extends Google Cloud’s powerful data processing and ML capabilities to gateways, cameras, and end devices, “making IoT applications smarter, more secure and more reliable.”
It lets you execute ML models trained in Google Cloud on the Edge TPU or on GPU- and CPU-based accelerators. Cloud IoT Edge can run on Android Things or Linux OS-based devices.
