Science Alert  July 29, 2022 Despite the prevalence of computing power and artificial intelligence, the process of identifying the hidden state variables themselves has resisted automation. Most data-driven methods for modelling physical phenomena still rely on the assumption that the relevant state variables are already known. A longstanding question is whether it is possible to identify state variables from only high-dimensional observational data. Researchers at Columbia University proposed a principle for determining how many state variables an observed system is likely to have, and what these variables might be. They demonstrated the effectiveness of this approach using video recordings of […]