Core Insights - The article discusses the transition of large models from a focus on parameter competition to a practical application in various industries, emphasizing the importance of integrating technology into real-world scenarios [1][2][10] - Companies are increasingly adopting vertical large models tailored to specific industries, moving away from generic models that lack depth in specialized fields [2][4][10] Group 1: Industry Trends - Leading companies are accelerating the penetration of large models into vertical industries, with examples including Huawei Cloud in steel manufacturing and Alibaba Cloud in mining [2][4] - The shift from "showcasing technology" to "practical application" is evident, as companies seek to address real business challenges rather than merely pursuing technical advancements [2][4][10] Group 2: Case Studies - The "Lingzhu Zhigong" model developed by Ningxia Jiaojian demonstrates a significant improvement in efficiency, achieving a 40% higher accuracy in specialized tasks compared to generic models [5][7] - Financial institutions are also benefiting from large models, with over 50% of China's top 100 banks partnering with Zhongguancun KJ to enhance service efficiency [7][8] Group 3: Strategic Approaches - Zhongguancun KJ's "platform + application + service" strategy aims to provide a comprehensive framework for the implementation of vertical large models, ensuring they are integrated into core business operations [9][10] - The focus on building cross-disciplinary teams and accumulating high-quality data is crucial for the successful deployment of AI technologies in various sectors [6][9] Group 4: Future Outlook - The integration of vertical large models is expected to transform industries by enhancing operational efficiency and driving innovation, marking a significant shift from experience-driven to data and AI-driven approaches [9][11] - The article concludes that the ongoing efforts in smart transformation will position the Chinese industry on a path toward high-end, intelligent, and green development [11]

Group 1 - The event "AI+ Innovation Cooperation Meeting" was held in Nanning, Guangxi, focusing on AI collaboration between Beijing and Guangxi [1][5] - Chen Gang, Secretary of the Guangxi Zhuang Autonomous Region, emphasized the importance of AI capability construction and encouraged enterprises to participate in the China-ASEAN AI Innovation Cooperation Center [3][6] - Zhongguancun KJ has actively engaged in Guangxi's "AI+" initiatives, conducting industry research and launching various AI model projects tailored to local industries [2][4] Group 2 - Zhongguancun KJ is recognized as the only company leveraging domain-specific models to be listed in the "2024 Hurun China AI Companies Top 50" [4] - The company employs a "platform + application + service" strategy to accelerate the implementation of vertical AI models across various sectors [4] - Notable collaborations include the development of the "Lingzhu" platform for the engineering sector and the "Baihe" model for the shipbuilding industry, showcasing comprehensive AI solutions [4]

编辑部 发自 凹非寺 量子位 | 公众号 QbitAI 大模型技术加速向产业渗透，如何直击业务痛点、带来真实增效？ "平台＋应用＋服务"是企业大模型落地的最佳路径。 在第三届AIGC产业大会上， 中关村科金总裁喻友平 分享如上方法论。 即使看似简单的需求，也需要经历需求拆解、数据调优与流程重构的闭环。在这个过程中，企服厂商需要提供好服务。 为了完整体现喻友平的思考，在不改变原意的基础上，量子位对演讲内容进行了编辑整理，希望能给你带来更多启发。 中国AIGC产业峰会是由量子位主办的AI领域前沿峰会，20余位产业代表与会讨论。线下参会观众超千人，线上直播观众320万+，累计曝光 2000万+。 话题要点 认知型AI亦遵循"C端先行、B端深化" 大模型技术正从消费端向产业端加速渗透； 认知性AI同样遵循"C端先行、B端深化"的路径； 企业需要端到端的解决方案而非孤立技术模块； 算法开源趋势使得数据主权愈加重要； 企业大模型落地最佳路径就是做好"平台+应用+服务"。 各位嘉宾下午好，非常荣幸受邀参与量子位大会的分享。此前各位专家已就前沿技术展开深度探讨，我的主题则聚焦于 大模型在企业服务领 域的落地实践——如何通过技 ...