Epoch AI’s training compute estimates get the New York Times visual treatment

A new visualization maps the staggering math behind AI models, drawing on Epoch AI's estimates of training compute and capability scores The New York Times has turned Epoch AI’s research into a visualization showing just how much math goes into training a modern AI model. The piece draws on Epoch AI’s estimates of training compute and capability scores. Epoch AI measures training compute in FLOP, short for floating-point operations. Each FLOP is a single arithmetic calculation involving decimal numbers. According to Epoch AI, training compute for frontier language models has grown at roughly 5x per year since 2020 . That works out to a doubling roughly every 5.2 months. The longer view is similar.

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