Most cognitive models are domain-specific, meaning that their scope is restricted to a single type of problem. The human mind, on the other hand, does not work like this – it is a unified system whose processes are deeply intertwined. In this talk, I will present our ongoing work on foundation models of human cognition: models that cannot only simulate, predict, and explain behavior in a single domain but instead offer a truly universal take on our mind. Together with a large international consortium, we have transcribed data from over 170 experiments – covering all major areas of cognitive psychology, including reinforcement learning, memory, decision-making, probabilistic reasoning, and many more – into a text-based form. We then used this data set to finetune a large language model, thereby aligning it to human behavior. The resulting model provides a window into human cognition and can be used for rapid prototyping of behavioral studies, to improve traditional cognitive models, and to generate new hypotheses about human information processing.