AI data center
In plain wordsA building or campus packed with AI chips, power equipment and cooling, built to train and run AI models. The biggest use as much electricity as a city.
A data center designed primarily for AI training or inference, distinguished from conventional cloud facilities by much higher power density, accelerator-dense racksrack-scale system, n.: An AI computer designed as one whole cabinet of chips, cooling and wiring, rather than separate servers, so all the chips inside can work together like one big chip. and specialized networking. Where traditional racks draw roughly 5–15 kW, AI racks draw 40 kW to well over 100 kW, which forces liquid coolingliquid cooling, n.: Cooling computer chips by running liquid past them instead of blowing air. AI chips now run so hot and are packed so tightly that air alone can no longer keep them cool., heavier floors and new power distribution. The largest campuses under construction in 2025–2026 target 1 to 5 gigawatts — for example Meta's Hyperion in Louisiana, Amazon's Project Rainier for Anthropic, OpenAI's StargateStargate, prop. n.: A giant venture announced in 2025 by OpenAI, SoftBank and Oracle to build data centers in the United States for training and running AI, with a pledged $500 billion. sites and xAI's Colossus in Memphis. Grid connections, transformers and turbines, more than chips, have become the main constraint on new capacity, prompting on-site gas generation and nuclear power deals. The International Energy Agency estimated that all data centers used about 415 TWh in 2024 (about 1.5% of world electricity) and projected roughly 945 TWh by 2030, with AI the main driver of growth. Facility efficiency is tracked with power usage effectivenesspower usage effectiveness, n.: A score showing how much of a data center's electricity actually reaches its computers: total power drawn divided by the computers' share. A perfect 1.0 would mean no waste; the extra goes mainly to cooling..
The binding constraint on the new AI data center isn't GPUs; it's a 300-megawatt grid connection.
Origin
Data centers grew from the mainframe computer rooms of the 1960s and the server farms of the internet era. The AI-specific category and name spread from about 2023, after ChatGPT set off a surge of GPU purchases and record capital spending by cloud providers.
Usage note
Environmental and local effects — electricity prices, emissions, water use and noise — are covered under environmental impact of AIenvironmental impact of AI, n.: The effects of AI on the planet: the electricity, water, materials and land used to make chips, build data centers and train and run models, and the pollution that results.. Nvidia's Jensen Huang calls such facilities 'AI factories'.
Related
- AI supercomputerAI supercomputer, n.: A huge network of AI chips — often tens or hundreds of thousands — wired together in a data center to train the largest AI models.
- rack-scale systemrack-scale system, n.: An AI computer designed as one whole cabinet of chips, cooling and wiring, rather than separate servers, so all the chips inside can work together like one big chip.
- liquid coolingliquid cooling, n.: Cooling computer chips by running liquid past them instead of blowing air. AI chips now run so hot and are packed so tightly that air alone can no longer keep them cool.
- power usage effectivenesspower usage effectiveness, n.: A score showing how much of a data center's electricity actually reaches its computers: total power drawn divided by the computers' share. A perfect 1.0 would mean no waste; the extra goes mainly to cooling.
- environmental impact of AIenvironmental impact of AI, n.: The effects of AI on the planet: the electricity, water, materials and land used to make chips, build data centers and train and run models, and the pollution that results.
- StargateStargate, prop. n.: A giant venture announced in 2025 by OpenAI, SoftBank and Oracle to build data centers in the United States for training and running AI, with a pledged $500 billion.
- computecompute, n.: The raw computing power used to train and run AI, usually measured by how many specialized chips are used and for how long. With data and algorithms, it is a main driver of AI progress.
- sovereign AIsovereign AI, n.: A country's ability to build and run AI on its own terms, so that the computers, models and know-how it relies on cannot be withheld or dictated by foreign companies or governments.
Sources
- International Energy Agency (2025). Energy and AI. IEA, Paris. iea.org/reports/energy-and-ai/executive-summary
Mentioned in
AI bubbleAI bubble, n.: The worry that investors are pouring far more money into AI companies, chips and data centers than AI will earn back soon, so that prices could crash as in the dot-com bust of 2000., America's AI Action PlanAmerica's AI Action Plan, prop. n.: The Trump administration's 2025 strategy for winning a global AI race: cutting regulation, building data centers and power plants quickly, and exporting American AI technology to allies., computecompute, n.: The raw computing power used to train and run AI, usually measured by how many specialized chips are used and for how long. With data and algorithms, it is a main driver of AI progress., environmental impact of AIenvironmental impact of AI, n.: The effects of AI on the planet: the electricity, water, materials and land used to make chips, build data centers and train and run models, and the pollution that results., Jensen HuangJensen Huang, prop. n.: The Taiwanese-American co-founder and chief executive of Nvidia, whose graphics chips became the main engine for training and running modern AI., StargateStargate, prop. n.: A giant venture announced in 2025 by OpenAI, SoftBank and Oracle to build data centers in the United States for training and running AI, with a pledged $500 billion., AI factoryAI factory, n.: A data center built to turn electricity and data into AI models and AI answers at industrial scale; in Europe, also a public supercomputing hub that helps companies and researchers build AI., AI supercomputerAI supercomputer, n.: A huge network of AI chips — often tens or hundreds of thousands — wired together in a data center to train the largest AI models., edge AIedge AI, n.: Doing AI's computing on or near the devices that collect the data, such as cameras, cars, factory machines, phones or local servers, instead of sending everything off to distant data centers., Epoch AIEpoch AI, prop. n.: A research nonprofit that gathers data on how fast AI is advancing — the computing power, data and money behind it — and publishes forecasts and difficult tests for AI., hyperscalerhyperscaler, n.: One of the few giant technology companies — such as Amazon, Microsoft, Google and Meta — that run vast networks of data centers and spend most of the money that builds AI computing., liquid coolingliquid cooling, n.: Cooling computer chips by running liquid past them instead of blowing air. AI chips now run so hot and are packed so tightly that air alone can no longer keep them cool., neocloudneocloud, n.: A newer kind of cloud company that mainly rents out powerful AI chips, rather than the full range of computing services that giants like Amazon or Microsoft sell., sovereign AIsovereign AI, n.: A country's ability to build and run AI on its own terms, so that the computers, models and know-how it relies on cannot be withheld or dictated by foreign companies or governments., AI Now InstituteAI Now Institute, prop. n.: A research and advocacy group that examines who is harmed by AI and argues that the deeper problem is the power of a few big technology companies, which it wants curbed by law., circular dealcircular deal, n.: A business arrangement in which an AI chip or cloud supplier invests in, or lends to, a customer that then spends the money buying the supplier's own products., CoreWeaveCoreWeave, prop. n.: An American company that rents out huge numbers of Nvidia graphics processors over the internet to AI developers such as Microsoft, OpenAI and Meta., Green AIGreen AI, n.: A movement to make AI research and products use less energy and computing power, and to report those costs openly alongside accuracy., orbital data centerorbital data center, n.: A proposed computer center circling the Earth, powered by almost constant sunlight, that would run AI without using land, water or power grids on the ground., power usage effectivenesspower usage effectiveness, n.: A score showing how much of a data center's electricity actually reaches its computers: total power drawn divided by the computers' share. A perfect 1.0 would mean no waste; the extra goes mainly to cooling., rack-scale systemrack-scale system, n.: An AI computer designed as one whole cabinet of chips, cooling and wiring, rather than separate servers, so all the chips inside can work together like one big chip.