New and evolving hardware technologies are making real-time AI inferencing at the edge a reality. These include fluid edge-to-cloud connectivity, expansive networking capabilities, and sustained computational performance at efficient power consumption levels, all of which are designed into Premio’s RCO-6000-CFL AI Edge Inference Computer.

Premio Inc. released the RCO-3000-CFL small form factor pc, adding to its flagship line of RCO fanless computing solutions. Its purpose-built ruggedized hardware is designed to bring computing intelligence into challenging, dynamic environments, closer to the source of data generation.

In the world of manufacturing for industrial and rugged applications, including robotics, and artificial intelligence, the Made in America moniker brings a lot of cache.

There’s been a lot written lately about the need for AI inferencing at the edge of the IoT.

Premio Inc. announced support for 5G connectivity in its RCO-6000-CFL family of industrial edge computers.

What Are The Top Hardware Needs For Edge Computing? 

As the number of IoT and IIoT devices continues to increase, so does the volume and velocity of data being generated. Edge computers are deployed to alleviate the burdens placed on the cloud and data centers. What are the hardware needs for edge computing? Here are the top 5 key features.