Artificial Intelligence (AI) technology enables devices and machines to perceive, reason, and act intuitively based on awareness of the situation. AI intends to enhance cognitive human abilities and covers a set of dissimilar problem areas that could involve ambiguous inputs and outputs that are thus difficult to compute (or even check for correctness).

The Internet of Things (IoT) connects devices that exchange data with other devices and systems over the internet. To enable intelligence on these connected devices, machine learning-based solutions would need to run on them. On-device intelligence or running AI algorithms (also called inferences) on the device as compared to on the cloud has various benefits such as low response latencies, increased reliability/privacy, and efficient use of network bandwidth. It is possible to achieve the best overall system performance by benefitting from high-speed connectivity and high-performance local processing. AI thus fuels the IoT expansion and a few AI-powered IoT use cases that benefit from higher edge processing are facial recognition, object and inventory tracking, scene classification, navigation and obstacle avoidance, smart cameras and displays and voice UI in today’s wearables. Efficient processing of diverse compute workloads with minimal power usage on a compact device is optimum for IoT propagation.

AI is fueling exciting innovation for the Internet of Things (IoT), and it’s driving a push toward high performance edge processing. On-device AI can make user experiences like travel and wellness, more intuitive and productive. When combined with trained algorithms, user history, and dedicated AI accelerators in the cloud, your devices could provide helpful recommendations and personalized AI-enabled experiences.