Building world models to match true system dynamics—rather than just optimize for control rewards—gives you smaller, more interpretable models that work better and reveal how environments actually function.
World2vec learns compact world models that accurately capture how environments actually work, not just predict well enough for control. By focusing on faithful dynamics reproduction rather than reward optimization, it achieves better performance with 10x fewer parameters than existing methods, enabling both better control and scientific discovery of system properties.