Recently scientists and tech companies have been exploring concepts and technologies to bring artificial intelligence closer to the edge. Ai On The Ede otherwise known as Edge Ai is a concept where AI runs on small devices, independent of internet connection.
Explained another way, Edge AI is a concept where intelligence and data processing is done locally on small devices, instead of via the cloud. Some analysts believe we are witnessing the emergence of a decentralized AI market. The edge is where a lot of money is being invested right now, and putting AI on the edge will continue to have tremendous value and impact. Today, there are startups and tech giants alike that are fully committed to creating infrastructure for a smarter edge and bringing self-learning AI to the edge.
The appeal for Ai Edge services is obvious, as it will allow industrial equipment, driver-less cars, drones etc to be functional even when they are offline. Imagine a countryside farm at a remote location. This countryside farm might have limited access to AI applications because of their poor connectivity etc, however with Edge Ai, they can benefit tremendously from the technology. As IoT moves into more disconnected environments, the necessity of edge will become more prevalent. No one is expecting that Edge computing will replace the Ai cloud, however Edge Ai is aiming to make AI’s operation model closer to that of how humans operate, which is by perform routine and critical decisions at the edge and then refer to the cloud in instances where more intensive computation or more detailed information and analysis is needed.
Another appeal for Ai Edge is as it relates to the sensitivity and privacy of information. Sending and storing so much information via the cloud can present security and privacy challenges.
Microsoft is putting a lot of emphasis on artificial intelligence and edge computing. They are introducing a lot of their existing Azure services to machines that sit at the edge, whether that’s a large industrial machine or a remote oil-drilling platform. Via their Azure IoT Edge, a collection of tools that brings AI, Azure services and custom apps to IoT devices, Microsoft is investing heavily in the space.
Microsoft will allow developers to develop software for the Intelligent Edge. At Microsoft Build developer conference, they announced a partnership with Qualcomm, one of the largest mobile and IoT chipset manufacturers in the world, to create a vision AI developer kit. This will empower Qualcomm’s latest AI hardware accelerators to deliver real-time AI on devices without the need for constant connectivity to the cloud or expensive machines.
We’re also now starting to see the emergence of external AI processors, for example the Movidius Neural Compute Stick, which provides deep learning computing at the edge. A recent partnership between ARM and Nvidia seeks to bring advanced deep learning capabilities to AI chips used in billions of devices such as smartphones, tablets that reside at the edge.
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