FEATURE : ENERGY
Generative AI ’ s demand for computing power will be limited by the inability of power utilities to expand their generation capacity fast enough and data centre administrators must include power supply limitations into expansion , pricing models and workload planning says
Bob Johnson at Gartner .
The explosive growth of new hyperscale data centres to implement Generative AI is creating an insatiable demand for power that will exceed the power utilities ’ ability to provide it . New , bigger data centres are being planned to handle the huge amounts of data needed to train and implement the continuously expanding large language models that underpin popular Generative AI applications . Data centre managers are realizing that there will not be enough power available to implement their most ambitious plans . increases as the largest data centre operators compete financially for scarce power resources .
Data centres that demand huge amounts of power can be built far faster than power utilities can expand their capacity . Delivering increased power to data centre locations often requires new transmission lines from existing generation facilities , which can take years for permits , but can even necessitate building new power plants , which can take decades .
Short-term solutions to provide more power often conflict with zero-carbon sustainability goals . Data centres require 24x7 power availability , which renewable power such as wind or solar cannot provide without some form of alternative supply during periods when they are not generating power . Truly 24x7 reliable power can only be generated by either hydroelectric power , fossil fuel or nuclear power plants .
Hydropower is limited by appropriate sites , and fossil fuel plants that had been scheduled to be retired are being kept operating in response to increased data centre power needs .
This problem is exacerbated by regional concentrations of data centres , which can consume a major percentage of the local power utility ’ s total production . Such concentrations benefit from wellestablished communication infrastructure , but can also threaten to overwhelm the power utility ’ s future capacity with expansion plans .
The situation is serious enough that some locations , such as Ireland and Singapore , are either severely limiting or completely stopping data centre growth out of power concerns .
Cost of power
The growth in number and computational power of Generative AI data centres , along with the infrastructure that supports them , requires ever increasing amounts of electrical power . Demand is quickly approaching the limits of the global electrical power industry ’ s ability to provide sufficient generating capacity .
The total estimated power demand for the collection , analysis , computation , storage and communication for global information and communication technology , is growing significantly faster than the total electrical energy production . Total ICT electricity demands will exceed 9 % of total global energy production by 2030 , up from less than 3 % today .
The inevitable result of impending power shortages is an increase in the price of power , which will also increase the costs of operating Generative AI ’ s large language models . Data centre operators can expect major cost
To satisfy this increase in demand , ICT applications would have to take considerable amounts of electricity from other areas , such as residential , commercial or industrial users . This is an untenable situation .
Power shortages will soon limit growth of Generative AI
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