Explore a 51-minute lecture on linguistic interaction in humans and machines presented by Yoav Artzi from Cornell University at the Simons Institute. Delve into the challenges of understanding contemporary machine learning models and their similarities to studying human cognition. Discover how methodologies from cognitive science are adapted to analyze ML models and vice versa, creating new tools for studying human cognition. Examine four language-focused projects that alternate between machine learning and cognition, offering insights into human adaptation in linguistic interactions and the generalization and adaptation of ML models. Gain a deeper understanding of the exciting potential in synthesizing these fields to advance our knowledge of higher-level intelligence from AI, psychology, and neuroscience perspectives.