Autonomous systems, such as robots and self-driving cars, have rapidly evolved over the past decades. Recently, foundation models have emerged as a promising approach to building more generalist autonomous systems due to their ability to learn from vast amounts of data and generalize to new tasks. The motivation behind this workshop is to explore the potential of foundation models for autonomous agents and discuss the challenges and opportunities associated with this approach.