Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

Understanding information processing in the brain—and creating general-purpose artificial
intelligence—are long-standing aspirations of scientists and engineers worldwide. The …

We consider the problem of sequential manipulationand tool-use planning in domains that
include physical interac-tions such as hitting and throwing. The approach integrates aTask …

Primates are highly attuned not just to social characteristics of individual agents, but also to
social interactions between multiple agents. Here we report a neural correlate of the …

We explore the hypothesis that many intuitive physical inferences are based on a mental
physics engine that is analogous in many ways to the machine physics engines used in …

Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

Early research in the field of intuitive physics provided extensive evidence that humans
succumb to common misconceptions and biases when predicting, judging, and explaining …

Humanity has regarded itself as intellectually superior to other species for millennia, yet
human cognitive uniqueness remains poorly understood. Here, we evaluate candidate traits …

Mental disorders arise from neural and psychological mechanisms that have been built and
shaped by natural selection across our evolutionary history. Looking at psychopathology …

Humans are able to seamlessly integrate tactile and visual stimuli with their intuitions to
explore and execute complex manipulation skills. They not only see but also feel their …