In the era of rapid technological advancement, Edge AI emerges as a transformative force, bridging the gap between traditional Artificial Intelligence (AI) and localized computing. But what exactly is Edge AI, and how does it work? In this blog, we dive into the world of Edge AI to understand its definition, functionality, use cases, and its potential impact.
Edge AI is the application of AI in a distributed computing framework that stores data sources close together. In simpler terms, it is the practice of placing data storage and devices/servers close together combined with the power of AI. AI allows data to be processed with or without an internet connection within milliseconds, which results in quick usage and competent features.
Edge AI works because it doesn’t rely completely on cloud storage. Devices can work on the network edge, and the proximity allows for quick transference. While cloud-based operating systems may have occasional delays, and often rely on non-local transmitting of data, Edge AI can take advantage of data that is close to its device. It sounds complicated, but you probably are using this technology daily!
Edge AI takes advantage of cloud systems while also efficiently using local operation. Each of these examples demonstrate placing the data adjacent to the device, allowing for it to be processed on an Edge AI platform. Here’s some common use cases and how they work:
Think of your smart device’s facial recognition, and how it works with or without access to the internet. Because it can use AI algorithms, data is processed in real time, and the immediacy of device to data allows this information to flow on its own platform of sorts. Issues that come from cloud-based processes can be minimized from having data local to receiver, and artificial intelligence can process said data without having to connect to various distant locations. That said, reliance on such a platform is not always so simple.
As with any form of connectivity, there is always the potential for challenges to arise. Because of its platform and method of data transference, Edge AI devices can frequently be restricted in computational resources, which results in difficulty implementing complex AI models. Moreover, the increased number of Edge AI devices paired with its limitations can make any wide-range device update an entire challenge on its own. Experts may focus on enhancing the AI model itself to combat these issues, as it is critical to create capable and powerful AI from the start when employing this form of connectivity. Nevertheless, this technology has proven to be cutting edge in its abilities.
Edge AI is an innovative and growing form of connectivity. As device capability and AI models continue to improve, we can be certain that Edge AI will be applied in revolutionary ways in the years to come.
At KORE, we work hard to provide a competitive suite of leading deployment services that bring efficiency and value to your business. Learn more about device connectivity here, or schedule a meeting with a KORE expert to discuss how Edge AI can be beneficial to your company’s success.