Probabilistic Programs Which Make Common Sense

Explore the intersection of probabilistic programming, artificial intelligence, and cognitive science in this thought-provoking conference talk. Delve into the historical foundations laid by George Boole and Alan Turing, and discover how their work on probabilistic inference and automated reasoning has evolved into modern probabilistic programming. Learn about Sigma, a functional programming language designed for creating probabilistic models. Understand how Sigma programs can be run forward for tasks like 3D scene rendering, and more intriguingly, how they can be run conditionally or in reverse to infer 3D scenes from 2D images. Examine the combination of functional programming with statistical inference, program analysis, and constraint solving that makes this possible. Consider the potential of probabilistic programming to unify concepts in logic, artificial intelligence, and cognitive science, bringing us closer to Turing's vision of a machine with common sense.

"Probabilistic Programs Which Make (Common) Sense" by Zenna Tavares