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Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts
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Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts
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Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts
Data-powered enterprises use data, analytics, and AI to fulfill their corporate purpose, achieve their business objectives, and drive innovation. And in today’s shaky world, they need to be like water to get there: adaptive by design, hyper-agile, super-responsive. There’s a place they find themselves increasingly to build and use these water-like capabilities: At the very outskirts of the business, far from central governance and IT, close to clients, partners, employees, the shop, the factory, the truck. It’s out there in the field where up-to-date data needs to be collected in real-time, analyzed on the spot, and turned into split-second actions, without being dependent on a corporate backbone that simply is too slow and too far away.
Edge AI – the use of AI in physical devices and all sort of other ‘things’ – is a perfect enabler for these new dynamics: Equipped with sensors and microprocessors, even the tiniest of things can collect data, analyze it with powerful AI algorithms (such as deep learning) and turn it into immediate action. And all of that is done with specialized technology that is typically inexpensive and has a small footprint in terms of power consumption. Moreover, it doesn’t depend on a continuous, high-bandwidth connection to a central network.
Not all organizations may yet bet their future on Edge AI, if only because there is a minimum number of physical assets involved in their business model. Even then, current developments in Edge AI hold key business lessons about how to become water-like ‘at the edge’ of the enterprise – think about autonomous decisions, real-time responsiveness, saving energy, infinite scalability, data security, privacy compliance, and always-on availability.
Also, if nothing else, Edge AI use cases are simply compelling and inspiring. We have selected seven of our favorite examples to whet your appetite:
The small robotic helicopter
It seems Ingenuity stole the show, right? The small robotic helicopter made history with its first powered, controlled flight by an aircraft on another planet. Yet, it was brought to Mars by Perseverance. The rover managed to land safely with its unique Terrain Relative Navigation, using AI image recognition to select a non-hazardous landing site in real-time. Not something that you can manage centrally, as the communication latency between Mars and Earth is 20 minutes. It’s a powerful metaphor, showing how to achieve critical business responsiveness and adaptability without centralized control.
IBM’s Mayflower Autonomous Ship
In ancient times, people believed that oceans marked the edge of a flat world. Indeed, quite an appropriate place to pioneer with Edge AI. IBM’s Mayflower Autonomous Ship is cramped with sensors and intelligent devices. First, to navigate the vast ocean with no one on board, avoid obstacles, learn how to reach the next harbor. But also to collect and analyze key environmental data, for example regarding the whale population, microplastics, and ocean chemistry. The enterprise lesson: Breakthrough, innovative insights are for the grab night and day at the edge of business. And no hands on deck needed to get it done.
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