Interest in edge computing continues to build, as does confusion surrounding the architecture. The situation is similar when it comes to artificial intelligence. The prospect of moving AI to the edge might sound like a recipe for even more confusion.
Performing artificial intelligence at the edge is often “just theory quoted in articles,” said Martin Davis, managing partner at DUNELM Associates.
Still, the concept of edge AI is increasingly hard for industrial and enterprise organizations to ignore. Resource-intensive operations such as deep learning and computer vision have traditionally taken place in centralized computing environments. But the growing availability of high-performance networking and computing hardware opens up the possibility to shift that activity a “centralized cloud architecture to the [edge],” as consultant Chaitan Sharma wrote.
Read the rest of Brian Buntz’ article on ITPro Today.
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