Michael I. Jordan, Pehong Chen Distinguished Professor in the Department of Electrical Engineering and Computer Science and the Department of Statistics at the University of California, Berkeley, recently visited the Yahoo campus in Santa Clara to give a talk entitled "Learning Natural Language Semantics." Talk Abstract: What is the total population of the ten largest capitals in the US? Answering free-form questions such as this requires modeling the deep semantics of language. But is it possible for a learner to acquire these deep semantics from only surface-level supervision, e.g., question/answer pairs? We answer affirmatively, by developing a new tree-based semantic representation with favorable linguistic and computational properties, along with an algorithm that induces this hidden representation. Using our approach, we obtain significantly higher accuracy on the task of question answering compared to existing state-of-the-art methods, despite using less supervision. (Joint work with Percy Liang and Dan Klein).