In what sense does a large language model (LLM) have knowledge? We answer by
granting LLMs 'instrumental knowledge': knowledge gained by using next-word generation …

What do we want from machine intelligence? We envision machines that are not just tools
for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and …

The processes underwriting the acquisition of culture remain unclear. How are shared
habits, norms, and expectations learned and maintained with precision and reliability across …

Abstract Theory of mind (ToM) broadly refers to humans' ability to represent the mental
states of others, including their desires, beliefs, and intentions. We design a Theory of Mind …

Goals play a central role in human cognition. However, computational theories of learning
and decision-making often take goals as given. Here, we review key empirical findings …

Neuroscience has focused on the detailed implementation of computation, studying neural
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …

Social learning is often portrayed as a passive process of copying and trusting others. This
view, however, does not fully capture what makes human social learning so powerful: social …

We review the idea that Theory of Mind—our ability to reason about other people's mental
states—can be formalized as inverse reinforcement learning. Under this framework …

Infants understand that people pursue goals, but how do they learn which goals people
prefer? We tested whether infants solve this problem by inverting a mental model of action …