“ Gartner predicts that by 2022, 80 percent of smartphones on the market will have on-device AI, and thatʼs up from just 10 percent in 2017.”
Gartner
Edge AI or AI at the edge is the use of AI techniques embedded in Internet of Things (IoT) endpoints, gateways and other devices computing data at the point of use. CIOs can leverage edge AI and edge computing with augmented and virtual reality, autonomous things, connected cards, digital twins, smart factories, geolocation sensors and visual image recognition. For the business it can raise innovation capabilities, operational excellence and customer engagement.
While cloud solutions get all the headlines right now, latency matters, and waiting on data centers miles away to power instant decision-making on site is not feasible for many applications.
Edge computing is the answer in many cases. Emerging advancements in the hardware and modules needed to push progress in AI at the edge fuel the possibilities. Edge devices and gateways-to-edge devices are now more powerful and enable the local collection, storage and analysis of data without waiting for value to be derived from the cloud and then passed back to the device. By combining AI and edge computing, IoT solutions are more powerful because the latency issues associated with cloud computing are eliminated.
Machine learning and data processing in the cloud wonʼt go away, but on-device AI is what is making connected devices, including automobiles, HD cameras, smartphones, wearables, and other IoT devices, smarter and faster.
CforXL 