在圆桌讨论中，光大信托普惠金融部副总经理祝世虎表示，中小金融机构的 AI 转型无需追求宏大蓝图，应聚焦 "轻量化" 路径，集中力量突破关键环节，具体可从三方面推进： 一是大数据轻量化，强调大数据的核心价值并非单纯追求数据体量的庞大，而是聚焦精准、高效的数据分析应用；二是大 模型轻量化，大模型可分为底座通用大模型、中间层行业级金融大模型及上层企业级大模型，中小机构应立足自身需求选 择适配的模型层级，避免盲目跟风；三是员工使用轻量化，需简化大模型操作流程，降低使用门槛，让员工能快速上手运 用技术赋能业务。 12月26日，由金融界主办、宁波银行支持、清华大学经济管理学院中国金融研究中心提供学术支持的"启航·2025银行业高质 量发展年会"在北京成功举办。本次年会以"凝心启新，聚力致远"为主题，汇聚监管专家、学界精英、行业领袖及科技企业 代表，围绕服务实体经济、数字化转型、AI+金融创新、风险防控等议题展开深度讨论，为银行业高质量发展建言献策。 ...

Investment Rating - The report maintains a "Buy" rating for several key companies in the semiconductor and AI sectors, including 中芯国际 (SMIC), 海光信息 (Haiguang), and others, indicating strong growth potential in the domestic AI and computing landscape [5][6]. Core Insights - The domestic AI landscape is witnessing significant advancements with the emergence of models like 豆包 (Doubao) and DeepSeek, which are leading the charge in multi-modal and lightweight AI model development, respectively [1][2]. - The report highlights a shift towards domestic computing power solutions, with chip manufacturers rapidly adapting to the evolving AI ecosystem, particularly through advancements in semiconductor processes and AI training capabilities [2][3]. - There is a notable increase in capital expenditure among cloud computing firms, driven by the rising demand for AI computing infrastructure, which is expected to lead to a "volume and price rise" scenario in the cloud computing market [3][4]. Summary by Sections Section 1: Breakthroughs in Domestic AI Models - 豆包 has emerged as a leading multi-modal model, enhancing capabilities in speech, image, and code processing, with a significant release of its visual understanding model in December 2024 [1][11]. - DeepSeek focuses on lightweight model upgrades, achieving a remarkable cost-performance ratio with its DeepSeek-V3 model, which has 671 billion total parameters and costs only 557.6 million USD, positioning it among the world's top models [1][12]. - The rapid iteration of domestic models, including updates from 通义千问 and others, reflects a competitive landscape that is accelerating the development of AI applications [1][34]. Section 2: Advancements in Domestic Computing Power - 中芯国际 is advancing its semiconductor processes, with N+1 and N+2 technologies being developed to support the growing demand for AI chips, achieving significant performance improvements [2][56]. - The report notes that the domestic chip industry is evolving, with companies like 昇腾 (Ascend) and others making strides in AI training and inference capabilities, thereby reducing reliance on international competitors [2][59]. - The cloud computing sector is experiencing a capital expenditure boom, with companies like 华勤 and 浪潮 rapidly deploying servers that are compatible with domestic computing power solutions [3][4]. Section 3: Infrastructure and Supply Chain Developments - The report emphasizes the need for enhanced computing infrastructure to meet the surging demand for AI applications, with significant investments being made in server and power supply innovations [3][4]. - Innovations in power supply and cooling systems, particularly the shift from traditional air cooling to liquid cooling, are becoming essential to support the increasing power density in data centers [4]. - The report identifies key players in the supply chain, including companies in power supply, cooling, and server manufacturing, that are poised to benefit from the growth of the AI and computing sectors [5].