Status quo of large-scale models, risks and challenges, and recommended countermeasures

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.