Pioneering AI methods are revolutionizing materials science, including semiconductor thin-film growth and composite material design. Collaborations between institutes are integrating large language models with molecular beam epitaxy systems to autonomously optimize Gallium Nitride semiconductor growth. Concurrently, novel AI-driven models aid in predicting composite properties with reduced data requirements, accelerating material discoveries crucial for biotech and electronics.