In conclusion, ML can facilitate the automated design of molecules and materials, despite some outstanding challenges. Its ability to quickly analyze massive datasets, identify patterns and make predictions surpasses that of physics-based methods. Automation without any prior knowledge makes it a handy tool to solve a variety of scientific problems. Ongoing research and advancements in ML techniques, combined with efforts to improve data availability and model interpretability, are likely to further enhance the impact of ML in this field.