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As AI continues to push the boundaries of perception and decision-making, robotics emerges as one of its most exciting and demanding playground. In this talk, we’ll explore how the intersection of machine learning and robotics opens up powerful avenues for interaction, manipulation, and embodied intelligence. We will emphasize the critical role of real-world experimentation and data collection in bridging the gap between simulation and deployment. Interestingly, tasks traditionally viewed as complex, like locomotion, have seen significant progress, while seemingly simple behaviors—such as dexterous manipulation—remain open challenges. By grounding AI systems in physical environments, we gain deeper insight into their capabilities and limitations, and identify new directions for research at the intersection of learning, control, and embodiment.
