【摘要】 大模型不仅关乎科技创新，也深嵌国家安全、经济转型与社会治理。文章分析了大模型发展现状、风险挑战及应对策略，以期为我国应对全球人工智能竞争、推动技术创新提供理论和政策启示。研究表明，大模型市场竞争激烈，行业渐趋整合。中美大模型竞争愈加呈现地缘政治博弈的特征。技术层面，大模型规模化效应递减，混合专家模型带来模型效率提升，思维链技术提升了大模型的逻辑推理能力。然而，大模型也面临技术内生、外部治理和社会衍生风险。应从体系层次综合应对：基础层从人工智能基本要素出发，通过技术优化控制大模型风险；法律层构建权责适配的创新激励制度，为市场提供稳定的预期；社会层则从更广泛的社会维度进行风险规制。更多还原

【Abstract】 Large-scale models(large models) are not only central to technological innovation, but also deeply entwined with national security, economic transformation, and social governance. This study examines the status quo of large-model development, identifies the key risks and challenges, and proposes response strategies, aiming to provide theoretical and policy insights for China’s navigations in global artificial intelligence(AI) competition and advances technological innovation. The research indicates that competition in the large-model market is fierce, while the industry is gradually consolidating. Competition in large models between China and the United States has escalated into a form of geopolitical contest. From a technical perspective, the marginal returns of large-model scaling appear to be diminishing; mixture-of-experts approaches have improved model efficiency; and chain-of-thought techniques have enhanced logical reasoning within large models. Nevertheless, large models face multiple risks, including those emerging from technology itself, external governance issues, and broader societal impacts. A comprehensive systems-level approach is therefore needed. At the foundational level, risk is controlled via technical optimizations rooted in AI’s fundamental elements. At the legal level, an innovation-incentive framework should be established, aligning responsibilities with rights to provide stable expectations for the market. At the societal level, risk regulation should be undertaken from broader social dimensions.更多还原