目前，基于星辰大模型体系，中国电信的自研AI技术已经在公安、政务、应急、工业、能源等近十个 重点行业和领域实现了落地，成功赋能超过30家央企及多地政府机构。面向未来，中电信人工智能科技 有限公司与中国电信人工智能研究院（TeleAI）将持续深化AI核心技术攻关，拓展更多赋能场景。 以"星辰大模型体系"为支点，依托智传网（AI Flow)基础设施能力，目标撬动新质生产力落地千行百 业，为数字中国建设注入强劲动能。 编辑：刘润榕 星辰视觉大模型实现了亿级图像视频的秒级精准检索，日均调用量突破30亿次，其中基于知识的万物布 控技术 TeleSearch 2.0，可根据自然语言精准检索图片或视频，实现跨模态复杂语义理解、超万种目标 精准检索，已应用在城市治理场景、公共安全治理场景，协助公安、交警快速侦破众多复杂案件，赋能 多地市的防汛防涝、应急指挥救援、电动自行车入梯识别等场景，以AI之力守护公众安全。 星辰多模态大模型融合生成式能力，推出央企首个视频生成创作平台TeleStudio，面向公众提供文生 图，文生视频等创意服务，进一步降低AIGC应用门槛，普惠大众。在由戛纳电影节发起的 AI 电影评 选"AI Film ...

Core Viewpoint - The upcoming "14th Five-Year Plan" marks a critical phase for state-owned enterprises (SOEs) in China, as they face intensified market competition and the need for high-quality development, with digitalization and AI technologies offering new solutions for reform and transformation [1] Group 1: Challenges in SOE Reform - Efficiency Dilemma: SOEs struggle with complex internal management processes, leading to slow decision-making and lengthy project approval times, which can take weeks or even months [2] - Innovation Bottleneck: Many SOEs face severe product and service homogenization, failing to meet the diverse and personalized demands of consumers, particularly in emerging sectors [3] - Management Issues: The lack of a unified data management system results in data silos, making it difficult for SOEs to analyze and utilize data effectively for strategic decision-making [4] Group 2: Digitalization and AI as Solutions - Digital Process Reengineering: By implementing digital technologies, SOEs can streamline internal processes, significantly reducing project approval times from an average of 45 days to just 7 days, thereby enhancing operational efficiency [5] - AI-Driven Innovation: AI technologies can analyze consumer data from various channels to identify preferences and needs, enabling SOEs to develop targeted products and services, such as personalized medications in the pharmaceutical sector [6] - Data-Intelligent Decision-Making: The integration of digitalization and AI allows SOEs to conduct in-depth data analysis, providing management with scientific decision-making support, as demonstrated by a state-owned energy company optimizing production strategies through data insights [7] Group 3: Successful Practices - China Telecom: The development of an AI model that covers over 30 dialects has improved communication services for elderly and remote users, setting a benchmark for digital transformation in the telecommunications sector [8][9] - China Merchants Shekou: The implementation of an AIGC-based design system has led to reduced costs and improved efficiency in construction projects, showcasing a successful case of innovation in traditional industries [10] - Tieling Hanhe Group: The deployment of a smart management system in asset management has transformed the operational model from heavy asset holding to light asset services, providing a reference for SOEs in asset management reform [11] Group 4: Challenges and Responses - Data Security and Privacy Protection: Ensuring data security is crucial for SOEs, which must establish comprehensive data management systems to protect sensitive information from external threats [12] - Shortage of Technical Talent: The lack of skilled professionals who understand both business and technology poses a challenge for SOEs in their digital transformation efforts [13] - System Integration and Collaboration Issues: The coexistence of diverse systems within SOEs complicates the integration of digital and AI technologies, necessitating the establishment of unified technical standards and collaborative mechanisms [14]