This paper investigates a new method quantum mechanics to explore RNA structures and dynamics, which could potentially have a great impact on modern techniques to modulate individual molecules for medical purposes. By combining machine learning and quantum mechanical approaches, the authors created a new tool, called Deep-ONIOM, which is particularly effective in accurately predicting the complex conformational properties of RNA molecules. This approach provides valuable, data-driven insights into the structures and dynamical behaviors of RNA molecules.