We estimated trends in global inference capacity and found that token demand appears to be growing much faster than supply.

Lessons from GPT-5’s economics

Decentralized training over the internet promises to scale training to the limits of the internet.

We illustrate a decentralized 10 GW training run across a dozen sites spanning thousands of kilometers. Developers are likely to scale data centers to multi-gigawatt levels before adopting decentralized training.

OpenAI has the inference compute to deploy tens of millions of digital workers, but only on a narrow set of tasks – for now.

OpenAI focused on scaling post-training on a smaller model

Epoch AI researchers Jaime Sevilla and Yafah Edelman forecast AI progress to 2040: coding automation, 10% GDP growth, and wild uncertainty after 2035.

Our director explains Epoch AI’s mission and how we decide our priorities. In short, we work on projects to understand the trajectory of AI, share this knowledge publicly, and inform important decisions about AI.

We clarify that OpenAI commissioned Epoch AI to produce 300 math questions for the FrontierMath benchmark. They own these and have access to the statements and solutions, except for a 50-question holdout set.

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.