石化化工行业智能化转型再获助力 记者注意到，作为《意见》的细化，两个附件提到的具体措施与石化化工行业息息相关。《指引》提出 要推动石化化工行业提质增效。如综合利用大模型、数字孪生技术突破油气勘探开发、化工新材料研发 范式。深度融合油气生产作业、管网储运、化工工艺等工艺机理、专家经验、生产运行数据等，打造石 化化工行业大模型，推动大小模型融合应用，实现油田作业区及化工安全生产监测预警、设备预测性维 护、工艺流程自适应优化、产品质量预测等。构建行业高质量数据集、数据资源节点等数据基础设施， 支撑行业大模型、智能体训练与开发，提升复杂场景人工智能应用水平。《指南》则为企业智能化转型 升级提供实施路径和方法指引。 "2023年以来，行业重点企业积极探索人工智能应用，涌现出智能化工大模型、TPT时序大模型、昆仑 大模型等系列专用大模型，但仍存在高质量数据集建设进展缓慢、可靠性不足、基础支撑薄弱等问 题。"工信部石化化工行业数字化转型推进中心秘书长李渊源介绍说，而此次《指引》专门提到推动石 化化工行业提质增效，《指南》也给出初步的落地应用指引，建议企业进一步夯实自身数据基础，挖掘 人工智能高价值应用场景，实现企业智能化升 ...

Group 1 - The core viewpoint of the article highlights the strategic transformation of Zhongkong Technology towards industrial AI, which is seen as a necessary response to industry demands and trends [1] - The company faces challenges in balancing production efficiency and energy consumption in traditional process industries, which drives technological innovation [1] - Zhongkong Technology's TPT temporal model utilizes industrial AI technology and can be applied across various industrial scenarios, creating a significant technological moat [1] Group 2 - The Chinese government has introduced multiple policies to promote equipment upgrades and the intelligent transformation of the manufacturing sector, with industries such as oil, chemicals, and steel expected to complete equipment upgrades by 2027 [1] - The company anticipates a compound annual growth rate of approximately 2.3% in China's industrial automation market from 2025 to 2027, as it accelerates its transition to an industrial AI company [1] - The TPT model has already been implemented in several facilities, resulting in production efficiency improvements of 1% to 3%, with plans for comprehensive integration and upgrades of industrial AI products in the next 2-3 years [1]