A new paper proposes a research roadmap for NeuroAI, aiming to bridge the gap between neuroscience and artificial intelligence. It identifies fundamental capability gaps in current AI, including interaction with the physical world, learning efficiency, and energy consumption. The paper suggests that principles from neuroscience, such as co-design of body and controller and prediction through interaction, can address these limitations. It also calls for interdisciplinary training and community support to advance this field. AI
影响 Could lead to more capable and efficient AI systems by drawing inspiration from biological computation.
排序理由 This is a research paper published on arXiv proposing a new research direction. [lever_c_demoted from research: ic=1 ai=1.0]
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