Embedded systems are becoming increasingly powerful, enabling complex computing tasks to be performed at the edge of networks. This decentralized approach reduces latency, improves reliability, and enhances security by processing and analyzing data locally. The result is that today, processors capable of delivering many trillions of operations per second (TOPS) are not required to perform ML. In an increasing number of cases, the latest microcontrollers, some with embedded ML accelerators, can bring ML to edge devices. Not only can these devices perform ML, they can do it well, at low cost, with very low power consumption, connecting to the cloud only when absolutely necessary. In short, microcontrollers with integrated ML accelerators represent the next step in bringing computing to sensors such as microphones, cameras, and those monitoring environmental conditions, that generate the data upon which all the benefits of IoT are realized.