IoT and 5G are Pushing AI to the Edge
The emergence of 5G and the growth of IoT-based devices has created a demand for real-time data analysis that traditional cloud networks simply can’t provide.
Until recently, apps and devices that utilize AI and machine learning algorithms were reliant on the cloud, and many still are. The actual physical data center where the data is processed could be located thousands of miles away. No matter how “smart” the device may be, the data it collects still must make a round trip to the cloud and back, and the relay speed is limited. This is fine for activities such as finding relevant news, voice-to-text, simple image recognition, etc.
However, the emergence of 5G and the exponential growth of IoT-based sensors and devices has created a demand for real-time data analysis that traditional cloud networks simply can’t provide. A surgeon conducting remote surgery over a 5G network, for example, will be using AI-based technology that must analyze dozens of images and make numerous decisions per second. Even the slightest latency caused by a round trip to the cloud could be catastrophic.
Or take self-driving cars. Autonomous vehicles require instantaneous feedback from their environment to make decisions, and use AI to analyze massive amounts of data every millisecond. Or another booming AI use case – the proliferation of Smart Cities. Multiple interconnected networks of traffic sensors, surveillance cameras, drones, and other monitoring collect data in many different locations that needs to be analyzed in real-time to keep traffic moving and keep their citizens safe. The rapid growth in AI analytics, including facial recognition, object classification and behavioral analytics consumes more data than the cloud can be expected to handle.
Placing data analysis capabilities at the edge of the network – as close as possible to the sensors, devices, cameras, and generators that are crucial to your operations – gives you several advantages over cloud-based solutions. Reducing the amount of data sent to the cloud cuts out unnecessary data transfers, decreases response times, and ensures data and analysis on critical processes are as fast and up-to-date as possible. In short, putting AI at the edge rather than in the cloud will be necessary in a 5G, IoT-empowered world. As Gartner analyst Thomas Bittman points out his blog The Edge will Eat the Cloud:
“Latency matters. I’m here, right now, and I’m gone in seconds. Put up the right appealing advertising before I look away, point out the store that I’ve been looking for as I drive, let me know that a colleague is heading my way, help my self-driving car avoid other cars through a busy intersection. And do it now… The edge will create some serious winners and losers, both in terms of vendors and businesses. The edge can’t be ignored, because it could be a serious competitive advantage.”
And industry has taken notice. Companies like Dell and Microsoft have invested billions of dollars in IoT portfolios and edge computing services, shifting data processing and analysis closer to the point of need. Dell founder and CEO Michael Dell has even remarked that “The Edge will be everywhere and everything…Dell’s strategy now is to create the distributed infrastructure to move customers’ innovations into a continuous cycle of renewal, with the edge enabling real-time analytics on real events.”
To learn how Netrality’s interconnected edge data centers can support your edge strategy, contact us.