Optimizing power efficiency to bring AI to the end device

Artificial intelligence (AI) is core to making our devices smarter. With billions of connected devices, the only way to manage the tremendous amount of data created by all of these interconnections is for devices to be able to make decisions at some level independently of the cloud. As devices become more complex and perform an increasing number of real-time functions, they will also need to be able to learn (known as training in AI) and adapt to specific applications, users, and environmental conditions. To meet real-time requirements and lower operating costs, these functions will need to move on-device as well. The challenge for developers is to implement intelligence in these edge devices in a way that is efficient in terms of performance and power.