Probabilistic Programming News Today

New research from MIT automates the math for trading off risk and reward, in domains ranging from artificial intelligence to climate to finance, fixing errors made by deep learning systems.

MIT researchers discovered a new way to estimate the amount of information contained in a piece of data using probabilistic programming and probabilistic inference. The breakthrough entropy estimators open up new applications in medicine, scientific discovery, cognitive science, and artificial intelligence.

C3.ai Digital Transformation Institute (C3.ai DTI) today announced the third round of C3.ai DTI funded advanced research awards, focused on using artificial intelligence (AI) to harden information security

Joshua Tenenbaum, a professor at MIT, explains how neuro-symbolic systems can help to address some of the problems of current AI systems.

Last year we started down the new road of uncovering enterprise analytics with machine learning. This year will see an acceleration. Here are some trends to watch.

MIT researchers have used probabilistic programming and inverse graphics to develop a framework that enables computer vision systems to more accurately explain 3D scenes observed in 2D images.

Computer vision systems sometimes make inferences about a scene that fly in the face of common sense. For example, if a robot were processing a scene of a