Workflow
绿色数智化
icon
Search documents
香港股票市场IPO超越纽约成全球第一,内地造船航运低空企业积极布局
Sou Hu Cai Jing· 2026-01-03 07:06
2025年的香港资本市场,以一场创纪录的IPO热潮强势重返全球舞台中央。港交所全年新股集资额突破2858亿港元大关,更成功超越纽约证券交易所与纳 斯达克,夺得全球股票市场IPO集资额榜首第一,让港股成为中国活跃企业对接国际资本的核心枢纽。近年来,中国内地活跃的造船、航运、机器人、低 空、人工智能、高端制造等企业也积极布局香港股票市场。为应对活跃企业投融资需求,总部上海的国际船舶海工网将在第十二届中国(上海)国际技术 进出口交易会支持下在2026年6月举办科技金融与高端产业投融资上海国际论坛。咨询报名:china@ishipoffshore.com 或 chinabobli@126.com 2026年中国造船厂地图成功发布后继续赠送,德国和新加坡海事版开始编辑。 迎国庆中秋,700家精锐中国船厂上榜造船厂地图最新版在上海交付,导弹式快递 2025年12月2日,来自福建福州的A股上市公司国航远洋(920571.BJ)发布公告称,为锚定国际化战略发展,构建公司"绿色数智化"的远洋运力规模,增强 新能源船舶技术引领优势,深度融入"走向深蓝"海洋强国战略,精准对接国家"十五五"规划中绿色航运、交通强国建设的核心要求,提 ...
“AI+制造业”有何机遇和挑战,汽车产业这么看
Di Yi Cai Jing· 2025-10-25 06:25
Core Insights - The automotive industry is integrating AI across the entire manufacturing chain, but several bottlenecks remain, including the lack of model generalization [1][4][5] Application of AI in Automotive Manufacturing - AI is primarily applied in quality inspection, data collection, and support for office and logistics functions [2][3] - Companies like Changan Automobile focus on AI for visual quality inspection and precision measurement, while BYD is leveraging AI for data processing and technical perception [2][3] Challenges in AI Implementation - The complexity of AI applications in precision manufacturing is high due to the industry's need for accuracy and safety, leading to difficulties in model generalization and reuse [4][5] - Current AI applications are often point-to-point, focusing on specific environments or processes, which complicates the integration of AI tools across different scenarios [4][5] Talent and Organizational Issues - There is a gap in understanding between IT professionals and business experts, which hinders AI application [5] - Companies need to establish clear organizational structures and collaborative mechanisms to facilitate AI integration [5] Data Management and Governance - Effective data collection and governance are crucial for advancing AI applications in automotive production [5][6] - The automotive sector must enhance data credibility and processing to support AI initiatives [5] Drivers for AI Investment - AI is recognized for its potential to reduce costs and improve efficiency in manufacturing, but significant resources must be allocated to digital technology and AI model development [6][7] - Different manufacturing sectors exhibit varying levels of AI application demand, with automotive manufacturing facing unique challenges due to frequent model changes [6][7] Policy and Industry Support - Multiple provinces are releasing policies to promote AI development, with the automotive industry identified as a key area for AI-driven industrial advancement [8] - The Guangdong province has launched an action plan focusing on AI's role in enhancing the quality of manufacturing, particularly in the automotive sector [8]