Benchmarking world models and embodied agents in closed-loop interactive environments
Embodied AI represents a paradigm shift from static, single-turn AI systems to agents that actively interact with and learn from dynamic environments. This lesson explores the unique challenges and methodologies for evaluating embodied AI systems, focusing on the World-In-World benchmark platform and the shift from visual fidelity to task performance.