We welcome Kenji López-Alt, world-renowned chef and author of multiple New York Times bestselling cook books, including The Food Lab: Better Home Cooking Through Science. Kenji will discuss the creativity and science of the culinary arts with Indre Viskontas.

Recent advances in deep learning have produced models that far outstrip human performance in a number of domains. However, where machine learning approaches still fall far short of human-level performance is in the capacity to transfer knowledge across domains. While a human learner will happily apply knowledge acquired in one domain (e.g., mathematics) to a different domain (e.g., cooking; a vinaigrette is really just a ratio between edible fat and acid), machine learning models still struggle profoundly at such tasks. I will present a case that human intelligence might be (at least partially) usefully characterised by our ability to transfer knowledge widely, and a framework that we have developed for learning representations that support such transfer. The model is compared to current machine learning approaches.

What psychological mechanisms do primates use to engage in self-control, and what is the ultimate function of these skills? I will argue that a suite of decision-making capacities, including choices about the timing of benefits, evolved in the context of foraging behaviors and vary with ecological complexity across species. Then, I will examine how these foraging capacities can be generalized to solve novel problems posing temporal costs that are important for humans, such as cooking food, and can therefore underpin evolutionary transitions in behavior. Finally, I will present work testing the hypothesis that a limited future time horizon constrains the expression of other complex abilities in nonhumans, explaining the emergence of human-unique forms of social cognition and behavior.