Deploying AI at the Edge: From Operation to Automation

As companies increase the use of automation technologies in their factories, warehouses and other locations, they recognize the need for artificial intelligence technologies (such as machine vision to inspect for defects) that can guide decisions in real time. But in practice, companies are finding that cloud-based AI technologies are taking too long, and they need to move this decision-making process to the edge of the network. "We often see industrial use cases where manufacturers or OEMs tell me that they have to make that entire round trip, including the network, in a very small number of milliseconds," says Rita Wouhaybi, Senior AI Principal Engineer at Intel. "It makes it impossible against the law of physics to actually send that request to the cloud." Reducing the time for decisions and reducing the expense of data movement are two of the big reasons why companies are now deploying AI technologies at the edge.