Smarter Everything with ML and the IoT
ML applications have never been easier to build. Whether cloud or edge-based, developers have a number of tools at their disposal for adding machine intelligence to any connected product. But as our systems become more sophisticated and capable and a dependence on the cloud increases, the need for privacy grows, and every embedded system should be designed with privacy in mind. Thankfully, there are advances in the ML and communications space that prioritize privacy, by default, including edge-based ML inferencing and cellular for cloud connectivity. With edge-based ML, decisions happen on devices instead of the cloud. And with cellular connectivity, edge systems send only the results of ML processing to the cloud, as opposed to potentially private or sensitive raw data. When used together, these two approaches help developers build applications that are secure by default.