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But we’ve barely scratched the surface, many believe, and artificial intelligence has much more to offer. Ironically, one of the things that is preventing AI from realizing its full potential is the cloud, one of the main technologies that helped usher AI into the mainstream.
“The reason we still don’t see AI everywhere is not that the algorithms or technology are not there. The main reason is cloud dependency,” says Ali Farhadi, the CEO of Xnor, a Seattle-based AI hardware startup.
Edge AI, the collective name for hardware and software that enable the performance of AI tasks without a link to the cloud, has gained much steam in the past few years. And as Farhadi and many other experts believe, the edge (or the fog, as some like to call it) will unlock many new AI applications that weren’t possible before...
The limits of AI in the cloud
Costs are not the only problem of cloud-based artificial intelligence. In many settings, a connection to the cloud is either non-present or unstable. This limits some of the very important use cases of AI such as agriculture, where computer vision algorithms and other AI techniques can help in precision farming. But farms are usually located in areas where getting a stable broadband internet connection is a real challenge.
Another example is automated rescue drones, which need to work in environments where communications infrastructure is weak or has been damaged due to natural disasters. Again, without the AI cloud, the drones won’t be able to function properly.
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Source: TechTalks