Lots of things are being called “smart” these days — everything from light bulbs to cars. Increasingly, the smarts come from some form of artificial intelligence or machine learning.
AI is no longer limited to big central data centers. By moving it to the edge, enterprises can reduce latency, improve performance, reduce bandwidth requirements, and enable devices to continue to operate even when there’s no network connectivity.
One of the main drivers for the use of AI at the edge is that the sheer amount of data produced in the field would cripple the internet if it all had to be processed by centralized cloud computing solutions and traditional data centers.
“The need to send all of that data to a centralized cloud for processing has pushed the limits of network bandwidth and latency,” says Ki Lee, vice president at Booz Allen Hamilton.