Epoch AI is a nonprofit research institute that tracks and forecasts the trajectory of artificial intelligence by analyzing trends in compute, data, algorithmic efficiency, and capabilities. It produces leading databases and quantitative models to help policymakers, researchers, and funders understand the pace and impact of AI progress.
Epoch AI is a nonprofit research institute that tracks and forecasts the trajectory of artificial intelligence by analyzing trends in compute, data, algorithmic efficiency, and capabilities. It produces leading databases and quantitative models to help policymakers, researchers, and funders understand the pace and impact of AI progress.
People
Updated 04/03/26Funding Details
Updated 04/03/26- Annual Budget
- $5,000,000
- Current Runway
- -
- Funding Goal
- $3,000,000
- Funding Raised to Date
- $23,200,000
Org Details
Updated 04/03/26Epoch AI is an independent nonprofit research institute based in San Francisco, California, whose mission is to improve society's understanding of the drivers, progress, and impact of artificial intelligence. The organization began in 2021 as a volunteer collective led by Jaime Sevilla and six co-founders — Tamay Besiroglu, Lennart Heim, Pablo Villalobos, Edu Roldan, Marius Hobbhahn, and Anson Ho — who assembled and analyzed data on AI trends. Following the 2022 publication of their widely-cited paper "Compute Trends Across Three Eras of Machine Learning," the group formalized as Epoch Artificial Intelligence, Inc., a 501(c)(3) nonprofit, to scale up its research. Epoch structures its research across three dimensions. The first is Drivers: investigating the inputs that constrain or enable AI advancement, including training compute, inference compute, ML hardware efficiency, and data center infrastructure. The second is Progress: measuring AI capability development through independent benchmarking, including its Epoch Capabilities Index (ECI) and the FrontierMath benchmark, which tests frontier mathematical reasoning. The third is Impacts: forecasting AI's economic and societal consequences through quantitative models such as GATE (a macroeconomic model for AI automation effects) and population surveys. The organization maintains several leading publicly accessible databases, including an AI Models database tracking training compute and release dates for hundreds of models, a Frontier Data Centers tracker using satellite and permit data, an ML Hardware performance database, and a Companies database covering AI investment and organizational data. These datasets are widely used by researchers, journalists, and institutions including Stanford's AI Index. In 2025, Epoch raised $10.3 million and spent approximately $5 million, growing its active website user base to nearly 1 million annually and its newsletter to over 10,000 subscribers. The organization had 21 full-time staff as of the 2025 Impact Report and is led by Executive Director Jaime Sevilla. Epoch takes on commissioned research and advisory engagements with organizations including OpenAI, Google DeepMind, xAI, the UK Department of Science, Innovation and Technology, and U.S. Congress.
Theory of Change
Updated 04/03/26Epoch AI's theory of change holds that better empirical data and quantitative forecasts about AI progress will lead to better decisions by those with the most leverage over AI's trajectory — including policymakers, grantmakers, and AI researchers. By rigorously tracking compute scaling, algorithmic efficiency, and capability benchmarks, Epoch provides a shared factual foundation that reduces confusion and calibrates expectations about the pace and character of AI development. More accurate forecasts enable funders and governments to allocate resources more wisely, researchers to identify genuine bottlenecks, and policymakers to act with appropriate urgency. Epoch also increases transparency by publishing its data openly, briefing government bodies, and engaging the broader AI safety community, amplifying the epistemic impact of its research.
Grants Received
Updated 04/03/26Projects– no linked projects
Updated 04/03/26Discussion
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