证券日报网讯中控技术10月20日在互动平台回答投资者提问时表示，截至目前，公司已打造新一 代"Plantbot"AI+机器人智能运行架构，涵盖巡检与操作机器人，协作装备类机器人，供应链物流机器 人，以及面向工业领域的人形机器人4类机器人产品。其中面向工业领域的人形机器人作为PlantbotAI架 构下的前沿探索，具备类人形态与通用作业能力，可适应现有工厂人机环境，执行多场景复杂任务。依 托大模型驱动的任务规划与自主学习能力，未来将实现"一机多能"的灵活部署，为极端环境作业、技能 短缺岗位替代及工厂智能化跃迁提供解决方案。国务院日前印发的《关于深入实施人工智能+行动的意 见》明确提出，要加快推动人工智能与产业发展深度融合。而中控技术在"人工智能+工业"领域的最新 成果——时间序列大模型TPT2，正是响应这一号召，致力于解决流程工业中长期存在的安全生产、质 量优化、能耗控制等核心痛点，以可量化的经济效益为企业降本增效、防控风险，成为中国乃至全球工 业智能化进程中的标志性成果。 ...

格隆汇10月20日丨中控技术(688777.SH)在投资者互动平台表示，截至目前，公司已打造新一 代"Plantbot"AI+机器人智能运行架构，涵盖巡检与操作机器人，协作装备类机器人，供应链物流机器 人，以及面向工业领域的人形机器人4类机器人产品。其中面向工业领域的人形机器人作为Plantbot AI 架构下的前沿探索，具备类人形态与通用作业能力，可适应现有工厂人机环境，执行多场景复杂任务。 依托大模型驱动的任务规划与自主学习能力，未来将实现"一机多能"的灵活部署，为极端环境作业、技 能短缺岗位替代及工厂智能化跃迁提供解决方案。 国务院日前印发的《关于深入实施人工智能+行动的 意见》明确提出，要加快推动人工智能与产业发展深度融合。而中控技术在"人工智能+工业"领域的最 新成果——时间序列大模型TPT 2，正是响应这一号召，致力于解决流程工业中长期存在的安全生产、 质量优化、能耗控制等核心痛点，以可量化的经济效益为企业降本增效、防控风险，成为中国乃至全球 工业智能化进程中的标志性成果。 ...

Core Insights - Zhang Bo emphasizes the need for China to develop an artificial intelligence (AI) path that aligns with its unique characteristics and national conditions [2][7] - The current state of General Artificial Intelligence (AGI) is debated, with differing opinions on its timeline for realization, primarily due to varying definitions of AGI [3][4] AGI Development - AGI is defined by three standards: domain generality, task generality, and a unified theoretical framework [4][5] - Current AI models, while significant, are still in the early stages of AGI development and require integration with hardware and robotics for practical applications [5][6] AI Applications in Healthcare - The application of AI in healthcare varies significantly by task complexity, with diagnostic systems facing high demands for reliability and interpretability [5][6] - AI can enhance efficiency in lower-risk tasks like triage, but high-stakes areas like diagnostics require thorough understanding and validation by medical professionals [5] AI and Robotics - The robotics sector faces challenges related to reliability and cost, hindering widespread adoption [6] - Current humanoid robots are largely in the prototype stage, and their practical application is limited by high costs and reliability concerns [6] China's AI Development Path - China's AI development should avoid blindly following Western models and instead focus on solutions that meet local needs, such as favoring wheeled robots over humanoid ones in urban settings [7] - The high costs associated with AI in industrial applications are a significant barrier, but there is potential for cost reduction through engineering and algorithm optimization [7][8] Industry Insights - The prevalence of Tsinghua University-affiliated AI companies is attributed to decades of research and development, creating a robust ecosystem for AI innovation [7] - Identifying promising AI companies should focus on the capabilities of their leadership and the alignment of technology with business needs [7][8]