The internet of things and smart devices are everywhere, which means computing needs to be everywhere too. And this is where edge computing comes in, because as companies pursue faster, more efficient decision-making, all of that data needs to be processed locally, in real time—on device at the edge.

“The type of processing that needs to happen in near real time is not something that can be hauled all the way back to the cloud in order to make a decision,” says Sandra Rivera, executive vice president and general manager of the Datacenter and AI Group at Intel.

The benefits of implementing an edge-computing architecture are operationally significant. Although larger AI and machine learning models will still require the compute power of the cloud or a data center, smaller models can be trained and deployed at the edge. Not having to move around large amounts of data, explains Rivera, results in enhanced security, lower latency, and increased reliability. Reliability can prove to be more of a requirement than a benefit when users have dubious connections, for example, or data applications are deployed in hostile environments, like severe weather or dangerous locations.

Edge-computing technologies and approaches can also help companies modernize legacy applications and infrastructure. “It makes it much more accessible for customers in the market to evolve and transform their infrastructure,” says Rivera, “while working through the issues and the challenges they have around needing to be more productive and more effective moving forward.”

A compute-everywhere future promises opportunities for companies that historically have been impossible to realize—or even imagine. And that will create great opportunity says Rivera, “We're eventually going to see a world where edge and cloud aren’t perceived as separate domains, where compute is ubiquitous from the edge to the cloud to the client devices.”