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Sep. 16, 2025
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Jan. 16, 2026
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Sep. 4, 2025
How powerful will AI become, and how fast? Epoch develops quantitative forecasting models to project where AI is heading, from near-term trends in compute and capabilities to longer-term questions about AI timelines, including when AI might become truly transformative, a threshold sometimes discussed as artificial general intelligence (AGI) or transformative AI (TAI). Epoch examines the evidence behind these forecasts, and tracks what current trends reveal about future AI progress.
Give up at least one of: text only, short time horizon, easy to grade, and expert human superiority.
We investigate progress trends on four capability metrics to determine whether AI capabilities have recently accelerated. Three of four metrics show strong evidence of acceleration, driven by reasoning models.
Mostly right about benchmarks, mixed results on real-world impacts
Stanford economist Phil Trammell joins Epoch AI to explore AGI, growth, GDP limits, and what economic theory can tells us about the future of AI.
If scaling persists to 2030, AI investments will reach hundreds of billions of dollars and require gigawatts of power. Benchmarks suggest AI could improve productivity in valuable areas such as scientific R&D.
Epoch AI researchers Jaime Sevilla and Yafah Edelman forecast AI progress to 2040: coding automation, 10% GDP growth, and wild uncertainty after 2035.
Why don't AIs automate more real-world tasks if they can handle 1-hour ones? Anson Ho explores key capability and context bottlenecks.
In this Gradient Updates weekly issue, Ege discusses the case for multi-decade AI timelines.
In this podcast episode, two Epoch AI researchers with relatively long and short AGI timelines candidly examine the roots of their disagreements.
We introduce a compute-centric model of AI automation and its economic effects, illustrating key dynamics of AI development. The model suggests large AI investments and subsequent economic growth.
AI progress is accelerating, with next-gen models surpassing GPT-4 in compute power, driving major leaps in reasoning, coding, and math capabilities.
Epoch AI presents their first podcast, exploring AI scaling trends, discussing power demands, chip production, data needs, and how continued progress could transform labor markets and potentially accelerate global economic growth to unprecedented levels.
Economists have proposed several different approaches to predicting AI automation of economically valuable tasks. There is vast disagreement between different approaches and no clear winner.
Our new article examines why we might (or might not) expect growth on the order of ten-fold the growth rates common in today’s frontier economies once advanced AI systems are widely deployed.
AI’s potential to automate labor is likely to alter the course of human history within decades, with the availability of compute being the most important factor driving rapid progress in AI capabilities.
We have developed an interactive website showcasing a new model of AI takeoff speeds.
We summarize and compare several models and forecasts predicting when transformative AI will be developed.
I give visual explanations for Tom Davidson’s report, Semi-informative priors over AI timelines, and summarise the key assumptions and intuitions
I give a visual explanation of Ajeya Cotra’s draft report, Forecasting TAI with biological anchors, summarising the key assumptions, intuitions, and conclusions.
Projecting forward 70 years' worth of trends in the amount of compute used to train machine learning models.