A public guide to AI infrastructure
National facts · Local consequences
Explore data centers by state, see what evidence says about their benefits and environmental impacts, and understand the AI systems driving demand.
Browse by stateThe public guide
Use The Watt Line as a reference: find facilities, understand what they change locally, and separate what’s established from what’s still uncertain.
National view · Local evidenceWhat AI is, how generative AI works, and what “open-source AI” does and doesn’t mean.
Get the basics 02 / 03What facilities can bring, what they use, and what the evidence can actually establish.
Review the evidence 03 / 03Find facilities, who owns and operates them, and what is known about each site.
Open the directoryAI, in plain language
AI is a broad category of computer systems. The label alone does not tell you how a system works, how accurate it is, or what it costs to run.
NIST’s AI definitionNIST describes AI as machine-based systems that can make predictions, recommendations, or decisions toward human-defined objectives. Generative AI models can create text, images, audio, video, and other content from patterns in data.
NIST’s generative AI definition ↗Under the Open Source Initiative’s 1.0 definition, people must be able to use, study, modify, and share an AI system. The definition also calls for access to training-data information, source code, and model parameters. Downloadable weights alone do not establish that all those parts are open.
Read the Open Source AI Definition ↗Open licensing can enable inspection, adaptation, and sharing. It does not guarantee accuracy or safety. NIST documents risks for generative AI including false but confident outputs, privacy concerns, harmful content, and cybersecurity threats; how these apply depends on the model and use.
NIST’s generative AI risk profile ↗Data-center evidence
Effects differ by facility, community, power supply, cooling system, and local agreement. We assess each claim with the evidence that can confirm it.
No blanket score for every facilityBenefits to verify
Evidence: payroll and job reports, tax agreements, budgets, permits, and verified project disclosures.
Environmental & community effects
Measured values, projections, company claims, and unknowns will be labeled separately.
The 2025 U.S. report estimates data centers used 192 TWh of electricity in 2024, about 4.7% of U.S. electricity use. That national estimate does not describe any one facility.
Read the reportNational facility directory
Choose a state to explore publicly documented data centers, their named operators, and the environmental and community information available in public records.
This is a curated starting directory, not a complete census. The seed dataset names operators but does not separately identify site owners; missing environmental data remains unknown.
Loading the directory snapshot. Each profile distinguishes the named operator from ownership; missing environmental information remains unknown.
Select a state to view its records.
A method you can follow
We use the same source rules for benefits, costs, and claims about AI. We label estimates, company statements, measured outcomes, and gaps.
Read our principlesWhat exactly is being said, and what would count as evidence?
Start with original documents, public data, and peer-reviewed work.
Include relevant counter-evidence and disclose where sources disagree.
Separate established facts from estimates, gaps, and unanswered questions.
Built from the record
Readers should know where information came from, who produced it, and what it can—and cannot—establish.
The Watt Line
A public resource for understanding data centers, their local effects, and the AI systems they power—built from evidence readers can check.
Back to the beginning
Local discussion
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