第二个"5万亿元"工业大市，呼之欲出 苏州2026年规上工业总产值目标为突破5万亿元 每经记者｜杨弃非 每经编辑｜杨欢 深圳"过线"后，第二个"5万亿元"工业城市即将诞生。 1月4日，苏州举行"新年第一会"，对外宣布：2025年，苏州规上工业总产值预计达4.89万亿元，2026年 目标为突破5万亿元。这意味着，如果该目标达成，继2021年突破4万亿元后，苏州规上工业总产值将实 现5年再上一个万亿元台阶。 值得注意的是，这是苏州连续第三年"新年第一会"聚焦推进新型工业化，也是连续第二年在会上高规格 布局人工智能产业。 而更具仪式感的是，在辞旧迎新之际，苏州举行"OPC苏州之夜"跨年活动，向外正式宣介苏州人工智 能"十小虎"企业。 这很难不令人联想到2025年初名噪一时的杭州"六小龙"。当时，有人曾一度发出拷问：苏州拥有最完整 的人工智能产业链，为何未能诞生类似的先驱型创业企业？ 经过一年探索，苏州如何改变这一局面？对于即将步入下一个万亿元征程的苏州，又意味着什么？ "小虎"对阵"小龙" 经过一年的发酵，地方之间人工智能比拼似乎变得更加火热了。 引领这一波浪潮的浙江，先一步设下新擂台。上个月，浙江首次公布96家浙 ...

Group 1 - The investment community is excited about the successful integration of "quantitative + AI" following the rise of DeepSeek earlier this year, with leading domestic quantitative private equity firms actively engaging in the AI sector [1][5] - Various quantitative firms are adopting different strategies and styles in their AI pursuits, with some founders establishing tech companies targeting verticals like AI + healthcare, while others are increasing investments in AI labs or venture capital [1][3] Group 2 - Lingjun Investment, a major player in the quantitative space, has launched a tech company, Dianfu Technology, focusing on health consultation by structuring medical data with expert involvement [2][4] - Dianfu Technology aims to expand its applications from maternal and psychological health to areas like children's health and chronic disease management [2][4] Group 3 - Multiple quantitative private equity firms are exploring AI applications in vertical fields, with notable developments including the establishment of AI companies by founders from prominent firms [3][4] - For instance, Mingchao Investment's partner has founded Jiusi Technology, focusing on financial applications, while another firm, Nian Kong Technology, is working on general large language models [3][4] Group 4 - The trend of quantitative firms entering the AI space is evident, with companies like Jiukun Investment creating platforms to invest in AI, robotics, aerospace, and consumer electronics [4][5] - Jiukun Investment emphasizes collaboration in developing large models for various applications beyond finance [4][5] Group 5 - The integration of quantitative methods and AI is becoming a significant trend, with quantitative firms leveraging their data processing and model iteration capabilities to enhance AI development [5][6] - The shared methodologies between quantitative investment and AI, such as data-driven decision-making and iterative feedback loops, highlight the potential for synergy in these fields [5][6] Group 6 - Quantitative firms possess unique advantages in talent acquisition, favoring individuals with mathematical modeling and system thinking skills, which are crucial for AI development [6] - Future trends in the integration of quantitative methods and AI may include applications in healthcare, psychological support, personalized education, and financial consulting [6]

Core Insights - The article discusses the "72-hour AI Survival Challenge" organized by Wuyuan Capital, where participants from diverse backgrounds used AI tools to navigate daily life without traditional internet access [3][50] - The challenge aimed to explore the potential and limitations of AI in real-world applications, emphasizing the need for new interaction pathways between humans and AI [5][21] Group 1: Challenge Overview - The challenge took place from May 15-18, 2025, in Shanghai, involving participants like product managers, students, and developers [3] - Participants were equipped with a computer and basic AI tools, but all conventional internet and mobile applications were disabled, forcing them to redefine daily tasks using AI [10][4] Group 2: Participant Experiences - Participants created various projects, including an AI friend, a survival song, and virtual live streaming setups, showcasing the creative potential of AI [4][11] - Challenges included technical difficulties such as human verification processes, which hindered automation efforts [21][14] Group 3: AI Tools Utilized - The AI tools provided included general language models for text generation and interaction, programming aids for development, and multimodal generation tools for content creation [7][9] - Participants had to innovate and adapt these tools to complete tasks like ordering food and creating digital content [23][30] Group 4: Emotional and Social Implications - The challenge raised questions about AI's ability to understand human emotions and foster connections, highlighting the boundaries of AI in addressing loneliness and emotional needs [5][22] - Participants reflected on the nature of human-AI relationships, considering whether AI can fulfill emotional roles or merely serve functional purposes [29][28] Group 5: Future Perspectives - The event served as a microcosm for exploring the future of human interaction with AI, suggesting that AI could redefine relationships and collaboration in various contexts [52][53] - The insights gained from the challenge may inform future educational models and the evolving role of technology in daily life [52][50]