Agent AI represents a promising direction toward Artificial General Intelligence (AGI), enabling systems to perceive and act across diverse domains. It leverages large foundation models (LLMs and VLMs) to process multimodal data, offering a framework for reality-agnostic training. Agent AI systems can interact with physical and virtual environments, incorporating external knowledge, multi-sensory inputs, and human feedback to enhance decision-making. These systems aim to mitigate hallucinations and biases in large models by grounding them in real-world contexts. The field of Agent AI encompasses embodied and agentic aspects of multimodal interactions, extending beyond physical environments to virtual realities where users can interact with agents. Agent AI integrates with large foundation models to improve performance in tasks like gaming, robotics, and healthcare. It addresses challenges such as hallucinations, biases, data privacy, interpretability, and regulation. The paradigm emphasizes the use of LLMs and VLMs for task planning, action execution, and multi-modal understanding. Agent AI systems are designed to learn from diverse data sources, adapt to new environments, and improve through continuous interaction. The framework includes modules for environment perception, learning, memory, action, and cognition, enabling complex, adaptive behaviors. Agent AI has shown potential in various applications, including gaming, where agents can generate scenes and interact with users. In robotics, it enables task planning and execution using LLMs and VLMs. In healthcare, it supports diagnostic and therapeutic applications. The field also explores multimodal interactions, video-language experiments, and NLP tasks, emphasizing the need for ethical considerations and inclusive design. Agent AI aims to create systems that are not only technically advanced but also socially responsible, ensuring fairness, privacy, and accessibility. The integration of Agent AI with emerging technologies promises to revolutionize AI applications across industries, fostering a dynamic and inclusive research community.Agent AI represents a promising direction toward Artificial General Intelligence (AGI), enabling systems to perceive and act across diverse domains. It leverages large foundation models (LLMs and VLMs) to process multimodal data, offering a framework for reality-agnostic training. Agent AI systems can interact with physical and virtual environments, incorporating external knowledge, multi-sensory inputs, and human feedback to enhance decision-making. These systems aim to mitigate hallucinations and biases in large models by grounding them in real-world contexts. The field of Agent AI encompasses embodied and agentic aspects of multimodal interactions, extending beyond physical environments to virtual realities where users can interact with agents. Agent AI integrates with large foundation models to improve performance in tasks like gaming, robotics, and healthcare. It addresses challenges such as hallucinations, biases, data privacy, interpretability, and regulation. The paradigm emphasizes the use of LLMs and VLMs for task planning, action execution, and multi-modal understanding. Agent AI systems are designed to learn from diverse data sources, adapt to new environments, and improve through continuous interaction. The framework includes modules for environment perception, learning, memory, action, and cognition, enabling complex, adaptive behaviors. Agent AI has shown potential in various applications, including gaming, where agents can generate scenes and interact with users. In robotics, it enables task planning and execution using LLMs and VLMs. In healthcare, it supports diagnostic and therapeutic applications. The field also explores multimodal interactions, video-language experiments, and NLP tasks, emphasizing the need for ethical considerations and inclusive design. Agent AI aims to create systems that are not only technically advanced but also socially responsible, ensuring fairness, privacy, and accessibility. The integration of Agent AI with emerging technologies promises to revolutionize AI applications across industries, fostering a dynamic and inclusive research community.