A new multimodal neural network, TMolNet, has been developed to improve molecular property prediction, integrating task-awareness and chemical modalities. Led by Han, Tang, and Lu, this AI-driven method promises enhanced accuracy in predicting chemical behaviors and properties, offering valuable tools for drug discovery and materials science. This marks progress in computational chemistry leveraging deep learning.