本报讯 （记者梁傲男）11月18日，阿里巴巴新推出的AI应用千问APP，在公测上线次日便迅速冲入苹 果App Store免费应用总榜第四位，排名超越DeepSeek。其火爆人气一度导致服务器拥堵，"阿里巴巴千 问崩了"的话题登上热搜，官方则以"我好着呢"幽默回应，侧面印证了其公测首日的火热流量。 阿里方面表示，千问APP的战略目标是打造未来的"AI生活入口"，成为一个"会聊天能办事"的个人AI助 手。除了智能对话，"能办事"将是其核心发力点。目前，千问已能实现一句指令生成PPT等复杂任务， 并在实盘投资大赛中战胜过全球顶级模型。据透露，阿里计划将地图、外卖、订票、办公等各类生活场 景全面接入千问，构建更强大的办事能力。 千问APP的底气源于阿里Qwen系列开源大模型的强大性能和广泛影响力。自2023年全面开源以来， Qwen模型全球下载量已突破6亿次。近期发布的旗舰模型Qwen3-Max，在性能上已超过GPT-4、Claude 3 Opus等国际顶尖模型。 此次发布标志着阿里正全力进军AI to C市场。11月17日，阿里巴巴正式宣布"千问"项目，并将其视 为"AI时代的未来之战"。千问APP主打免费，并计划 ...

11月18日，阿里巴巴新推出的AI应用千问APP，在公测上线次日便迅速冲入苹果App Store免费应用总榜 第五位，排名超越DeepSeek。其火爆人气一度导致服务器拥堵，"阿里巴巴千问崩了"的话题登上微博热 搜，官方则以"我好着呢"幽默回应，侧面印证了其公测首日的火热流量。 此次发布标志着阿里正全力进军AI to C市场。11月17日，阿里巴巴正式宣布"千问"项目，并将其视 为"AI时代的未来之战"。千问APP主打免费，并计划与阿里生态内的各类生活场景深度结合，其目标是 与ChatGPT展开全面竞争。据悉，面向海外市场的千问APP国际版也将在近期上线。 千问APP的底气源于阿里Qwen系列开源大模型的强大性能和广泛影响力。自2023年全面开源以来， Qwen模型全球下载量已突破6亿次。近期发布的旗舰模型Qwen3-Max，在性能上已超过GPT-4、Claude 3 Opus等国际顶尖模型。英伟达CEO黄仁勋曾表示，Qwen已占据全球开源模型的大部分市场。同时， Qwen模型也正成为硅谷初创公司的技术基石，Airbnb CEO布莱恩·切斯基公开称公司正"大量依赖 Qwen"，因其比OpenAI模型更快更好。 ...

千问APP的底气源于阿里Qwen系列开源大模型的强大性能和广泛影响力。自2023年全面开源以来， Qwen模型全球下载量已突破6亿次。近期发布的旗舰模型Qwen3-Max，在性能上已超过GPT-4、Claude 3 Opus等国际顶尖模型。英伟达CEO黄仁勋曾表示，Qwen已占据全球开源模型的大部分市场。同时， Qwen模型也正成为硅谷初创公司的技术基石，Airbnb CEO布莱恩·切斯基公开称公司正"大量依赖 Qwen"，因其比OpenAI模型更快更好。 阿里方面表示，千问APP的战略目标是打造未来的"AI生活入口"，成为一个"会聊天能办事"的个人AI助 手。除了智能对话，"能办事"将是其核心发力点。目前，千问已能实现一句指令生成PPT等复杂任务， 并在实盘投资大赛中战胜过全球顶级模型。据透露，阿里计划将地图、外卖、订票、办公等各类生活场 景全面接入千问，构建更强大的办事能力。 此次发布标志着阿里正全力进军AI to C市场。11月17日，阿里巴巴正式宣布"千问"项目，并将其视 为"AI时代的未来之战"。千问APP主打免费，并计划与阿里生态内的各类生活场景深度结合，其目标是 与ChatGPT展开全面竞争。据 ...

Group 1: Core Insights - Artificial intelligence (AI) is a strategic technology driving a new wave of technological revolution and industrial transformation, recognized for its strong "leading goose" effect and as a key engine for cultivating new productive forces [1][2] - The Chinese government has prioritized AI development, with "AI+" included in the 2024 Government Work Report and a focus on fostering future industries through AI actions [1][2] - The AI industry is experiencing rapid growth, entering a high-speed development phase driven by technological innovation and commercial application [1][4] Group 2: Historical Development - The development of AI has gone through several phases, from initial exploration in the 1950s to significant breakthroughs in the 21st century, particularly with the rise of deep learning and applications in various fields [2][3] - The emergence of large-scale pre-trained models in 2020 marked a new stage in AI development, enabled by advancements in high-performance computing and the availability of massive datasets [4][5] Group 3: Industry Structure - The AI industry is divided into core industries, which include software algorithms, hardware products, and platform services, and fusion application industries that integrate AI into traditional sectors [6][9] - The core AI industry and fusion application industry mutually promote each other, leading to a relatively complete industrial system with continuous technological innovation and expanding investment [6][9] Group 4: Global Landscape - The United States leads in AI development, focusing on high-performance general models before penetrating vertical industries, creating a "top-down" development path [7][8] - In contrast, the European Union and Japan leverage their resource endowments and industrial foundations, with the EU focusing on data resources and regulatory frameworks, while Japan emphasizes AI integration with manufacturing [8][9] Group 5: China's AI Development - China's AI development emphasizes overall layout and industrial synergy, leveraging its comprehensive manufacturing base to prioritize application and industry collaboration [9][10] - From 2017 to 2024, China's core AI industry scale surged from 18 billion to 600 billion yuan, with over 4,700 companies and leading global positions in research output [10][11] Group 6: Application Scenarios - AI large models are primarily applied in voice assistants and intelligent customer service, with the intelligent customer service market reaching 3.94 billion yuan in 2023 [12][13] - In manufacturing, AI models enhance efficiency across the entire production chain, with applications in design, predictive maintenance, and quality inspection [14][15] Group 7: Challenges and Opportunities - The AI industry faces challenges in core technology breakthroughs and ecosystem construction, with a need for improved collaboration among large and small enterprises [16][17] - Despite significant investments, the AI sector in China is still developing, with a need for sustainable business models and effective integration of AI into various industries [18][19] Group 8: Future Directions - Future AI development in China will focus on top-level design, tackling key core technologies, and enhancing the industrial ecosystem to foster innovation and application [19][20] - Collaborative innovation in AI applications will be essential, with a focus on addressing common challenges across industries and promoting the integration of AI into various sectors [21]