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Agent AI refers to interactive systems that perceive visual, language, and environmental data to produce meaningful embodied actions in physical and virtual worlds. It aims to create sophisticated and context-aware AI, potentially paving the way for AGI by leveraging generative AI and cross-reality training. Agent AI systems often use large foundation models (LLMs and VLMs) for enhanced perception, reasoning, and task planning. Continuous learning is crucial for these agents to adapt to dynamic environments, refine their behavior through interaction and feedback, and achieve self-improvement.