GlobalData’s Decarbonizing AI Framework – Strategic Intelligence
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Rapidly growing AI-related energy consumption poses sustainability challenges. Energy consumption and the volume of greenhouse gas (GHG) emissions from the artificial intelligence (AI) value chain will constrain the potential growth of AI and threaten the environmental credentials of tech giants.
GlobalData’s decarbonizing AI framework identifies the areas where energy use and GHG emissions can be reduced. AI vendors and stakeholders can use this framework to pinpoint areas for decarbonization and implement energy efficiency strategies.
Scope
GlobalData’s decarbonizing AI framework identifies the areas where the energy use of AI-related activities can be reduced and outlines the strategies for achieving these reductions, thus enhancing the overall sustainability and operational efficiency of data centers (DCs).
The framework consists of three pillars. The energy source pillar examines how data centers (DCs) can shift to low-carbon energy. Various options are assessed, with renewable energy and small modular reactors (SMRs) emerging as the most viable solutions for sustainable power generation. The facilities infrastructure pillar addresses how DCs can be designed, built, and managed sustainably. The tech stack pillar focuses on improving AI model efficiency.
Key Highlights
Data centers are significant drivers of electricity demand. They run 24 hours a day, 365 days a year on a huge scale. In addition, power requirements for AI applications are rising sharply and are being reflected in data centers’ energy consumption.
Cooling and air conditioning systems are major consumers of energy, accounting for 40% of data centers’ energy demand. Traditional air-cooling methods used in data centers do not have the heat capacity needed to dissipate GPU workloads. This requires specialized cooling technologies. Otherwise, overheating of IT equipment can lead to failure and inefficiencies.
Reasons to Buy
GlobalData’s decarbonizing AI framework was designed to help companies identify areas where emissions can be reduced, and processes made more sustainable. Using this framework, stakeholders can pinpoint areas for improvement and implement tailored strategies to enhance energy efficiency and promote green practices across data center operations.
Alphabet
Amazon
Auras Technology
Constellation Energy
Delta Electronics
Device42
EirGrid
Equinix
Iceotope
Kairos Power
Liteon
Maruwa
Meta
Microsoft
Nautilus Data Technologies (NDT)
NuScale
NV Energy
Oklo
Qcells
Saft Batteries
Schneider Electric
Sunbird
TSMC
X-Energy
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