How AI at the Edge Is Defining Next-Generation Hardware Platforms

The Center for Advanced Electronics through Machine Learning (CAEML) has been very active in the newly-established machine learning track at DesignCon, helping to present many quality papers from the hardware design community. Celebrating its third anniversary this year, CAEML has been at the forefront of machine learning and its applications in hardware and electronic design. Much of the center's research has direct applications in the area of hardware and device management through machine-learned inference – from proactive hardware failure predictions, to complex performance modeling through surrogate models, to high dimensional time series prediction for resource forecasting. This article will take a look at some of the results of this research and its applications for AI-defined, next-generation hardware platforms. There has been an explosive growth of Internet of Things (IoT) devices in recent years. Analysts at Gartner predict the IoT will produce about $2 trillion US in economic benefit in the next five to 10 years.