Edu Roldán is a software engineer at Epoch AI. He helps maintain the website and assists researchers with programming tasks.

We investigate four constraints to scaling AI training: power, chip manufacturing, data, and latency. We predict 2e29 FLOP runs will be feasible by 2030.

Our expanded AI model database shows that training compute grew 4-5x/year from 2010 to 2024, with similar trends in frontier and large language models.

When could transformative AI be achieved? We present a simple, user-adjustable model of key inputs that forecasts the date TAI could be deployed.

We have developed an interactive website showcasing a new model of AI takeoff speeds.