EDGE AI HAS THE POTENTIAL TO HARK BACK TO ONE OF THE EARLY BENEFITS OF THE INTERNET IN DECENTRALISATION . BUILDING ON TRENDS SUCH AS BLOCKCHAIN , WEB3 AND THE METAVERSE , EDGE AI CAN ENABLE ARCHITECTURES WHICH ARE INHERENTLY RESILIENT , SELF- OPTIMISING AND HIGHLY EFFICIENT .
D A T A C E N T R E P R E D I C T I O N S
neural network , they can be referred to as Edge AI . Additionally , with video as a central Edge AI component , a vision processing unit microprocessor is preferred in many of these applications to accelerate Machine Learning and AI algorithms , to better support image processing ( or computer vision ) by using less power with higher speed .
Distributed IT or Edge Computing has been implemented in sectors such as retail and finance , and manufacturing will increasingly deploy Edge Computing to enable increasing use of Industrial Internet of Things ( IIoT ), as well as automation and more . The next 12 months or so will be when everyone starts talking about the need for Edge AI . This AI at the Edge will support not just optimisation of infrastructure and operations , it will also be key in supporting enterprise applications .
Moving to the Edge
In many cases , but already seen in the likes of retail , the day to day data is not as important as the insights it contains , which must be extracted quickly to be of value . Data processing has arguably been moving from the core to the Edge of networks over the last decade or so , and especially for Big Data applications for which the result is the key and raw data less so .
A raft of developments , from processor technologies to 5G and Wi-Fi 6 highcapacity networks , have enabled more and more applications to be placed at the Edge , providing vital speed and capability where it is needed . When these Edge implementations run AI algorithms in a
This kind of Edge AI has numerous benefits , not just to reduce data traffic to centralised infrastructure , which is in danger of experiencing the concept of data gravity , but in providing intelligence from data faster than previously . This in turn can feed into AI optimisation of operations with better quality inferences from fresh data direct from where it is produced .
Edge AI has the potential to hark back to one of the early benefits of the Internet in
Additionally , data centres are evolving to be able to provide an optimised foundation for the increasing AI workload demand from businesses of all sizes . Data centres truly are the unsung heroes of our digital future . �
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EDGE AI HAS THE POTENTIAL TO HARK BACK TO ONE OF THE EARLY BENEFITS OF THE INTERNET IN DECENTRALISATION . BUILDING ON TRENDS SUCH AS BLOCKCHAIN , WEB3 AND THE METAVERSE , EDGE AI CAN ENABLE ARCHITECTURES WHICH ARE INHERENTLY RESILIENT , SELF- OPTIMISING AND HIGHLY EFFICIENT .
decentralisation . Building on trends such as Blockchain , Web3 and the Metaverse , Edge AI can enable architectures which are inherently resilient , self-optimising and highly efficient .
Central role for data centres
Data centres have a central role to play in future demands of the digital world . Not only can they host AI-enhanced applications and services that can increase efficiency and provide the transparency to enable other industries and sectors to decarbonise , they can directly contribute to the acceleration of renewable energy adoption to achieve the pledges made by 118 governments at COP28 .
Steven Carlini , Vice President of Innovation and Data Center , Schneider Electric
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