Explorative Modeling Cuts Generative AI Compute 256×, Improves Sample Efficiency
The new Explorative Modeling paradigm adds a third pretraining axis, delivering up to 6.2× sample efficiency, 4.1× FLOP efficiency and 47% better parameter efficiency. It matches diffusion models on control tasks while using up to 256× less inference compute, slashing cost and speeding scaling.