AI+传统产业
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“AI+传统产业”实践应用发展论坛上,找钢网探索AI与传统产业融合新路径
Sou Hu Cai Jing· 2026-02-12 07:01
找钢网管理合伙人兼副总裁张晓坤在论坛上表示,找钢网及其合作伙伴有望成为第一批迈入"A2A"时代 的企业。"A2A"涵盖"Agent to Agent""Application to Application""Area to Area"三个层次,意味着找钢网在 自身拥抱AI的同时,会向产业链上下游辐射AI能力,打通产业链各环节"产品到人"的"最后一公里",把握新 型产业业态新需求。 例如,找钢网自研的SaleMatch交易引擎,早期技术不成熟时准确率不足,如今每天能处理1000万多条消息 量,解析准确率达到95%以上,并完成数亿级的智能交易匹配。2018年9月底,找钢网与腾讯共同投资成立 腾采科技公司,腾采通逐步将业务范围从钢铁拓展到其他价格波动快的工业原材料,就是找钢网AI能力跨 行业应用的生动体现。 另一方面,在通用大模型方向,找钢网与头部企业密切合作。不仅及时引入DeepSeep、千问等产品,还会将 使用体验及遇到的问题及时反馈给产品开发方,助力改进用户体验和技术缺点。此次论坛上,腾讯、阿 里、百度、京东均有代表出席,上一次BATJ齐聚还是在乌镇互联网大会,足见此次论坛的影响力。 2026年1月16日,由 ...
首届“AI+传统产业”实践应用发展论坛在上海举办 探索人工智能产业化路径
Zheng Quan Shi Bao Wang· 2026-01-19 08:20
Group 1 - The forum "AI + Traditional Industry" aims to explore the integration of artificial intelligence into traditional industries to drive high-quality development of the real economy [1][2] - The Vice President of the China Electronics Chamber of Commerce emphasized the importance of focusing on real application scenarios and building a sustainable collaborative ecosystem for AI integration [1] - The founder and CEO of Zhaogang Group highlighted the need for long-term viable application paths for AI in traditional industries, showcasing Zhaogang's efforts in embedding AI capabilities into key operational areas [2][3] Group 2 - The China Electronics Chamber of Commerce released the "2025 Artificial Intelligence Industry Development White Paper," which outlines the global AI industry landscape and key application directions [2] - Various industry leaders shared insights on AI's practical applications, indicating that AI has the potential to transform multiple sectors, including B2B growth and international trade [3][4] - A collaborative initiative was launched to promote standardization and ecological cooperation in AI applications across industries, involving multiple stakeholders from technology companies, academic institutions, and industry platforms [5]
首届“AI+传统产业”实践应用发展论坛举办 探索人工智能产业化路径
Zhong Guo Jin Rong Xin Xi Wang· 2026-01-17 01:32
Core Viewpoint - The forum highlighted the transition of artificial intelligence (AI) from isolated applications to deep integration with traditional industries, emphasizing the importance of real-world applications and sustainable collaborative ecosystems for driving high-quality development in the real economy [1][5][10]. Group 1: Forum Highlights - The forum "AI + Traditional Industries" was organized by the China Electronics Chamber of Commerce and foundry group, focusing on how AI can enhance industrial applications and promote economic transformation [1]. - Keynote speakers included representatives from various sectors, discussing the need for AI to move beyond concepts to establish long-term, replicable application paths within industries [5][9]. - The China Electronics Chamber of Commerce's AI Committee released the "2025 AI Industry Development White Paper," outlining the global AI landscape and providing guidance for government and enterprise practices [7]. Group 2: Industry Perspectives - The Shanghai Jiading District emphasized AI as a crucial driver for new productivity and development momentum, particularly in automotive and integrated circuit industries [3]. - Find Steel Network, as a platform rooted in the complex steel industry, has integrated AI capabilities into key operational areas, enhancing efficiency and collaboration [5]. - Industry leaders discussed the structural impact of AI on various sectors, including energy, light industry, infrastructure, healthcare, and electronics, highlighting the need for businesses to leverage AI for industry transformation [8][9]. Group 3: Collaborative Efforts - A roundtable discussion featured representatives from investment institutions, AI tech companies, and academia, focusing on the real-world effectiveness of AI in business and the importance of systematic integration into business processes [9][10]. - The forum concluded with a ceremony to launch initiatives for standardization and ecosystem collaboration, aiming to facilitate AI's sustainable application in industrial contexts [10][11].