Artificial intelligence is reshaping the world we live in and opening opportunities in commercial and industrial systems applications that range from autonomous driving and medical diagnostics to home appliances, industrial automation, adaptive websites and financial analytics. Next up is the communications infrastructure that links systems together, moving toward automated self-repair and optimization. For example, the U.S. Navy plans to expand its Consolidated Afloat Networks and Enterprise Services (CANES) ocean combat network with AI, connecting ships, submarines and on-shore naval stations.
These new architectures will perform functions such as load balancing and allocating resources for wireless channels and network ports based on predictions learned from experience. Applications they support demand high performance and, in many cases, low latency to respond to real-time changes in conditions and demands. They also require power consumption to be as low as possible, rendering unusable solutions that underpin machine-learning in cloud servers where power and cooling are plentiful. A further requirement is for these embedded systems to be always on and ready to respond even in the absence of a network connection to the cloud.
This combination of factors calls for a change in the way hardware is designed.
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