The paper proposes a framework for understanding the various roles of foundation models in decision making, including conditional generative models, representation learners, and interactive agents. Key takeaways include the use of foundation models for behavioral priors, world modeling, and generalization of knowledge across tasks and environments.

Read full paper: https://arxiv.org/abs/2303.04129

Tags: Artificial Intelligence, Machine Learning, Explainable AI