Core Insights - The establishment of a comprehensive product and service system by the China Mobile Qilu Innovation Institute is likened to a "central kitchen" for the AI industry, enabling tailored AI products and solutions based on diverse industry needs [1][3] - The Shandong provincial government is promoting high-quality products in the AI industry chain, aiming to enhance the new productive forces of artificial intelligence [1][3] Group 1: China Mobile Qilu Innovation Institute - The China Mobile Qilu Innovation Institute, a new R&D institution established by the Shandong provincial government and China Mobile, was inaugurated in July 2024 and has developed several innovative AI solutions within its first year [3] - The institute has created a full-stack capability system covering "network—computing power—data—model—platform—application—security—service," facilitating end-to-end service links [3] - The institute plays the roles of "supplier," "aggregator," and "operator" in the Shandong AI industry chain, promoting a collaborative ecosystem for AI development [3] Group 2: Inspur Group - Inspur Group's AI factory is recognized as China's first industrialized and standardized production line tailored for industry scenarios, addressing the demand for smaller, specialized computing power services [5] - The company is leading the industry in deploying large models across 68 sectors, positioning itself as the top player in China's industry large model market [5] Group 3: Zhenghe Technology Co., Ltd. - Zhenghe Technology has achieved several national firsts in cost reduction and efficiency enhancement through AI-driven services, transforming traditional service timelines from monthly to minute-level responses [7] - The company utilizes a combination of "large models + big data + software engineering" to significantly reduce the time required for tasks, thereby automating management processes and enhancing innovation efficiency [7] - Shandong's comprehensive industrial system is expected to experience significant growth in traditional industry upgrades and emerging industries due to the expansion of AI application scenarios [7]

Group 1 - The conference highlighted five major trends in artificial intelligence, including accelerated iteration of foundational large models, a shift in focus towards post-training and inference stages, deep collaboration between hardware and software, the rise of intelligent agents and the intelligent agent economy, the promotion of open-source ecosystems, and increasing demands for AI safety governance [1] - Beijing Economic-Technological Development Area is committed to building a comprehensive AI city, with plans to establish a national AI data training base, the largest public computing power platform in the city, and to implement special policies and funding exceeding 1 billion yuan to support major projects in various AI-related fields [1] - By the end of 2025, the development goals include opening 100 landmark application scenarios, gathering 600 core enterprises, and achieving an industry scale target of 80 billion yuan [1] Group 2 - The AI hardware and software testing and verification center was officially launched, aiming to provide key testing and verification capabilities for AI hardware and software, with four core capabilities established [2] - The center has partnered with major companies to create innovation labs and testing facilities to accelerate the innovation and prosperity of intelligent computing technologies [2] - Five major achievements in AI hardware and software collaborative innovation were announced, showcasing significant breakthroughs across the entire technology chain from foundational computing power to framework software [2] Group 3 - The center completed the first batch of testing and evaluation for the adaptation of large models and domestic hardware and software, with several companies successfully passing the evaluation [3] - The conference awarded certificates to institutions that passed the unified benchmark testing, marking a new stage in the standardized and quantifiable development of AI collaborative innovation ecosystems [3] - The AI safety governance initiative was highlighted, with 18 companies disclosing their safety practices, contributing to the establishment of a solid foundation for responsible AI development [3] Group 4 - The vice president of the China Academy of Information and Communications Technology emphasized the urgent need to address challenges in hardware and software collaboration for building an open intelligent computing ecosystem [4] - The AISHPerf 2.0 benchmark system was officially released, featuring upgrades to support multiple inference engines and domestic open-source model loads, addressing various evaluation needs [4] - The academy has initiated a series of collaborative testing and verification efforts based on AISHPerf, focusing on large model adaptation and key collaborative technologies [4]