EXPERT SPEAK
Key takeaways
• IDC projects global spending on Edge computing to be $ 232 billion in 2024 , an increase of 15.4 % from last year .
• Centralised data processing means longer routes between users and content and higher latency experienced by users accessing content .
• Service providers have turned to content delivery network architectures , deploying cache servers closer to users .
• Content delivery networks are only effective for frequently consumed repeatable data , and not economically viable for random workloads
• Machine decisions that need to be tightly synchronised require very low latency , that centralised compute infrastructure cannot deliver .
• By accelerating buildup of decentralised compute infrastructure , UAE and Saudi Arabia can bolster performance of AI-driven applications .
• A substantial part of that Edge compute demand will be comprised of GPU clusters to provide distributed AI inference .
• Delivering applications closer to the end user is a critical factor for AI applications .
• AI services cannot run inside everyday data centre servers and need computers with high-performance graphics processing units .
• High-performance clusters of graphics processing units running AI services need high-speed networks to move AIrelated data .
• High-speed and high-capacity data centre interconnect networks must remain front of mind for investment .
• Regional telcos can capitalise on the proximity to end users to process data closer to the source to support localised services .
• International Energy Agency forecasts , electricity consumption from data centres , cryptocurrencies , and Artificial Intelligence could double between 2022 and 2026 .
By accelerating the build of decentralised compute infrastructure , the UAE and Saudi Arabia can bolster the performance of AI-driven applications and boost the competitiveness of the region in this flourishing field .
In addition to delivering lower latency , this infrastructure can also help sensitive data stay in the region . AI models training , fine-tuning , or inference deals with data that might be preferred to be kept locally , rather than sent to a centralised location .
Even as core data centre buildouts continue to unfold across vast expanses of the world , the shift toward Edge data centres presents
both challenges and opportunities . For instance , the environmental impact of data centres cannot be ignored . According to an International Energy Agency forecast , electricity consumption from data centres , cryptocurrencies , and Artificial Intelligence could double between 2022 and 2026 .
Consequently , data centre projects are exploring various techniques to enhance sustainability in storage and processing to reduce the burden on existing power grids . This includes adopting the latest optical technology , implementing more efficient cooling methods , and utilising alternative power sources .
This is particularly critical in the Middle East , where there is heavy reliance on cooling systems to counter the effects of extreme heat . There is a shift to alternative power sources such as solar energy to enhance sustainability , with Masdar City in Abu Dhabi integrating sustainable practices into its data centre operations .
Delivering applications closer to the end user is a critical factor for AI applications . However , to realise these gains , the networks within , and between , data centres must be upgraded . Cutting-edge AI services cannot run inside everyday data centre servers ; they need computers with high-performance graphics processing units , GPUs .
And those high-performance clusters of GPUs running AI services need high-speed networks to move AI-related data inside a data centre and then out to the wider world . Outside the site , high-speed and high-capacity data centre interconnect networks must remain front of mind for investment .
Regional telcos can capitalise on the proximity to end users and the ability to process data closer to the source to support a plethora of localised services . It will result in ever more responsive business decision-making and an explosion in service innovation . •
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