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English(EN) AI Sovereignty as National Learning Capacity: A Human-Centered Learning Mechanics Viewpoint on France, the United States, and China

将人工智能主权视为国家学习能力

一篇新的观点论文提出,应通过“国家人工智能学习系统”的视角来理解国家人工智能发展。该框架基于以人为本的学习机制(HCLM),认为人工智能主权不仅源于规模,更源于一个国家管理其信息动态的能力。该论文提倡一种受控的增长策略,即信息注入的速度超过制度消散的速度,并为法国提供了政策指标和模拟。 AI

影响 提出了一种新的人工智能政策框架,将重点从规模转移到受控的信息动态以实现国家人工智能主权。

排序理由 该集群包含一篇讨论理解国家人工智能发展新理论框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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  1. arXiv cs.AI TIER_1 English(EN) · Kim Phuc Tran ·

    AI Sovereignty as National Learning Capacity: A Human-Centered Learning Mechanics Viewpoint on France, the United States, and China

    arXiv:2606.00729v1 Announce Type: new Abstract: Artificial Intelligence is often discussed in France in terms of investment, compute capacity, regulation, employment, sovereignty, and education. These dimensions are usually treated separately. This viewpoint paper proposes a unif…