I want to know how quickly AI's understanding about biological life grows.

If AI simulates a lifeform that is more heavy than an amoeba this question resolves to yes.

Any simulation must be shown to approximate molecule dynamics. If this information is latent then a interpretability technique should be able to extract it.

Any simulation is allowed to have prior information about laws of physics, basic chemical reactions and which molecules should be present but no description of how these molecules should be positioned so definitely not descriptions of entire organelles.

Any AI should learn its simulation from a self-supervised dataset composed of measurement data about at-the-time living amoeba (or heavier). This data may not be too pre-interpreted by a human, so no description of the state of the organelles, but rather pixel data from a video recording or water temperature.

I'll be likely to resolve this to yes if we're largely unsure about the workings of the simulation, but still got novel insights into protein folding from the few parts that we did understand. For this to happen the simulation should still be accurate.