What is an Edge AI Platform?


Dec. 10, 2021

When deploying real-world systems, it’s crucial to think about how the system will be built and structured. “Edge computing” is a hot computing trend that is reshaping the standard topology of distributed systems. So what is an edge AI platform, exactly, and what are the benefits of edge platforms for your business?

What is Edge Computing?

These days, a single distributed computing system may be composed of many different interconnected devices, not necessarily in the same physical location. The computers in this system work in conjunction to collect and analyze data and share the results with each other.

Until recently, however, devices that collected data typically had limited computing resources, making them inefficient for large-scale data analysis. Instead, these smaller devices sent their findings to a centralized server (often located in the cloud), which assumed responsibility for in-depth data crunching.

That has all changed with the introduction of the edge device. Edge devices are powerful enough to collect, store, and process data locally, instead of relying on other computers in the distributed system to do this work.

In the edge computing paradigm, the system prefers to perform the maximum amount of computation on edge devices, rather than on a remote cloud server. The advantages of using edge devices include:

  • Faster speeds and lower latency: In many use cases, data collected by edge devices needs to be analyzed immediately—which means you can’t afford to send this data to the cloud and wait for the results.
  • Decreased costs: Rather than having to pay for your use of the public cloud, you can help shrink your cloud IT footprint by offloading computation to edge devices.
  • Better data privacy: If you have concerns about sending confidential data to a third party, edge devices can help improve privacy by storing and processing this information locally.

One common use case for edge computing is edge AI. With cameras or sensors on edge devices, you can capture visual data and then rapidly analyze it using computer vision platforms and AI models. For example, edge AI can use a camera feed to perform real-time facial authentication, only allowing authorized individuals into a restricted area.

What is an Edge Platform?

We’ve discussed the general concept of edge computing—so what is an edge platform?

An edge platform is a solution that simplifies and streamlines the process of deploying and maintaining edge devices. If an edge platform is used for artificial intelligence applications, it’s known as an “edge AI platform.”

The functionality of an edge platform may include:

  • Developing and deploying software to run on edge devices.
  • Managing the edge devices in your edge computing network.
  • Directing traffic between sensors, cameras, and edge devices for maximum efficiency.
  • Automating the scaling process (up and down) during times of unexpected demand levels.
  • Providing real-time visibility into the edge network for cutting-edge insights and faster troubleshooting.

Why do businesses use edge platforms? Although there are many benefits of edge devices, not every organization has the technical know-how to implement an edge computing network for themselves. That’s exactly where edge platforms come in.

Edge platforms make it easier for businesses of all sizes, industries, and skill sets to leverage the power of edge computing. They offer a centralized interface for managing your edge devices and software.

For example, edge AI platforms can rapidly generate and deploy new AI models to your edge devices, offering greater flexibility and agility. Users can easily monitor and update all of the nodes in their edge computing network, as well as integrate them with the rest of their enterprise IT infrastructure. This makes the most use of the user’s edge computing AI and contributes to the success of the edge AI platform.