AI on the Edge

Digital transformations are being fuel-injected by leading enterprise tech like hybrid clouds, containers, and AI.

Adding to the acceleration is 5G, which is adding decentralized data and application processing from millions of endpoints outside the traditional datacentre and public cloud. But while transformation and modernization are bringing improved enterprise performance, efficiency, and agility, these increasingly complicated infrastructures are also complicating data management and availability, especially for AI workloads.

The AI on the Edge solutions from Nearby Computing helps run AI algorithms locally on an edge node (hardware device) where these algorithms are based on the data that are created on the device without requiring any connection. This allows you to process data with the device in less than a few milliseconds which gives you real-time information. AI processing today is mostly done in a cloud-based data centre with deep earning models that require heavy compute capacity. However, with AI on the Edge, processing is now moving part of the AI workflow to a device and keeping data constrained to an edge node.

Why is AI on the Edge important?

Moving the AI processing to an edge node brings about numerous benefits including reducing cost, increased security, highly responsive resulting in quick decision making and the ability to easily manage the data generated. The intelligent edge is a continually expanding set of connected systems and devices that gather and analyse data—close to end users and the data that is generated. Together, they give customers the ability to create a new class of distributed, connected applications that enable breakthrough business outcomes.