Why Artificial Intelligence Needs To Learn How To Follow Its Gut

When we look at a stack of blocks or a stack of Oreos, we intuitively have a sense of how stable it is, whether it might fall over, and in what direction it may fall. That's a fairly sophisticated calculation involving the mass, texture, size, shape, and orientation of the objects in the stack. Researchers at MIT led by Josh Tenenbaum hypothesize that our brains have what you might call an intuitive physics engine: The information that we are able to gather through our senses is imprecise and noisy, but we nonetheless make an inference about what we think will probably happen, so we can get out of the way or rush to keep a bag of rice from falling over or cover our ears. Such a "noisy Newtonian" system involves probabilistic understandings and can fail. Consider this image of rocks stacked in precarious formations.