The future of language learning

This podcast episode explores the fascinating similarities and differences between children learning language and AI systems learning language. The guest, Michael Frank, discusses the potential of artificial intelligence models to provide scientific insights into children's learning. While previous models were limited, advancements like ChatGPT have opened up new possibilities for understanding how to learn a natural language through data observation. The discussion highlights the question of what is responsible for the data gap between human learners and AI systems and the exciting scientific opportunities it presents. Additionally, the episode emphasizes the importance of social interaction and multimodal experiences in language acquisition, the relationship between language acquisition and social skills development in children, and the challenges of securing funding for global scientific projects. Overall, the episode underscores the importance of early language exposure, rich social interaction with language, and enjoyable and engaging language experiences for children.