近来，人工智能的快速发展，给平台经济带来了新的变化，也引发了对其健康发展的思考。截至今年6 月份，腾讯、阿里、抖音、百度等平台企业用户已超过10亿人，我国移动互联网人均单日使用时长和次 数分别提升至7.97小时和117.9次，平台经济早已是连接商户与消费者的关键纽带。《中共中央关于制定 国民经济和社会发展第十五个五年规划的建议》明确提出，完善监管，推动平台经济创新和健康发展。 如何更有效地让平台经济运行在科学健康的轨道上，成为题中应有之义。 种种因素表明，推动平台经济创新和健康发展，对促进经济发展有着非常重要的意义，但必须坚持发展 和规范并重。要在明确规则、划清底线的基础上，既注重监管，又不忽视企业本身的商业模式创新，建 章立制加以规范。 从监管层面来看，要加强对平台经济常态化监管，提升数据安全治理监管能力。数据是平台经济的关键 生产要素，要加快建立数据产权归属认定、市场交易、权益分配、利益保护机制，促进数据合规高效便 捷使用，充分发挥我国海量数据和应用场景优势。增强数据安全治理执法，优化数据安全治理惩处机 制，严惩重点领域数据违法犯罪行为，为数据安全治理营造良好环境。组建跨部门的专业执法队伍，充 实市场监管 ...

Core Viewpoint - The dialogue between Musk and Huang Renxun at the Saudi-US Investment Forum highlights the significant impact of AI on the future of work and the economy, raising questions about whether AI represents a bubble or a transformative future narrative [1][2]. Group 1: AI and Work - Musk envisions a future where work becomes optional and money loses its importance as AI and robots take over most jobs, leading to a scenario where basic material production is no longer scarce [3][4][5]. - The idea is that households will have humanoid robots to assist with daily tasks, and factories will be filled with robots producing goods continuously, resulting in lower prices for essential items [6]. - In this future, individuals will work not for survival but for personal fulfillment, choosing to work based on passion rather than necessity [7][8]. Group 2: The Concept of Money - Musk suggests that in an AI-driven world, the concept of money will gradually lose its significance, as machines will handle all production, potentially leading to a scenario where essential goods are free [11][13]. - Huang Renxun offers a more pragmatic view, stating that while AI will not eliminate jobs, it will change the nature of work, making low-value jobs obsolete and allowing individuals to focus on more valuable tasks [14][15]. Group 3: AI as Infrastructure - Huang Renxun argues that AI is fundamentally an infrastructure shift, moving from retrieval-based computing to real-time generative computing, which minimizes the space for a potential bubble [19][20]. - This transition indicates that AI is continuously evolving and optimizing, suggesting that concerns about an AI bubble may be premature [20]. Group 4: Investment Opportunities - The dialogue emphasizes the importance of identifying investment opportunities in AI, suggesting that individuals can either participate directly in the industry or invest financially [21][24]. - The tech giants in the US have seen significant market value, and the recent performance of tech stocks in both the US and Hong Kong indicates a strong trend towards technology investments [28][29]. - The ongoing technological advancements, particularly in humanoid robots, suggest that there will be substantial investment opportunities as these technologies become more widely implemented [32]. Group 5: Energy and AI - Both Musk and Huang Renxun agree that energy is a critical bottleneck for AI development, with increasing energy demands as AI technologies advance [36]. - This presents investment opportunities in energy sectors, particularly in regions upgrading their infrastructure to support AI, such as Saudi Arabia's plans to transform oil refineries into AI factories [39].

大埔宏福苑火灾通报：13人以误杀罪被捕，棚网阻燃多处不达标，调查仍在推进。 整理 ｜爆浆豆腐 点击上方【36氪随声听】，一键收听大公司热门新闻。听完音频记得添加进入 【我的小程序】 中哟！ 警方就香港大埔火灾已拘捕13人，罪名是误杀 香港特区政府12月1日下午介绍大埔宏福苑火灾搜救调查等最新情况。警方已拘捕13人，罪名是误杀。调查仍在进行中，不排 除更多人被捕。经警方实地调查搜证，在着火大楼中采集到7个地方的棚网样本，没有达到阻燃标准。（新华社） DeepSeek发布两个正式版模型 罗永浩否认给企业发产品比直播赚的多 俞敏洪接任东方甄选公司法定代表人 顺丰推出"超时赔付"服 务： 成本由公司承担，快递员无需承担 《疯狂动物城2》创年内进口片内地票房冠军 明年起新加坡中学生在校不能使用智能手机和手表 自2026年1月1日起，销售避孕药品和用具将依法征收增值税，不再享受免征增值税的优惠政策。目前施行的《中华人民共和国 增值税暂行条例》第十五条规定，避孕药品和用具免征增值税。而2026年1月1日起施行的《中华人民共和国增值税法》第二十 四条免征增值税的项目中，则不再设有"避孕药品和用具"这一项。 免征增值税政策的取 ...

中共辽宁省委关于制定辽宁省国民经济和社会发展第十五个五年规划的建议发布。其中提到，举全省之 力发展人工智能核心产业，加快工业软件创新突破，推动工业全要素智能化发展，构建覆盖算力、算 法、数据、应用的人工智能产业生态。深化与国内先进人工智能研究院所对接合作，协同发展通用人工 智能、生成式人工智能，支持智能运载工具、智能可穿戴设备、全屋智能产品、具身智能机器人等智能 硬件产品研发推广。 ...

Core Viewpoint - The Japanese government is preparing to inherit or restart the unfinished business of Asimo in the humanoid robot field, aiming to develop AI-driven humanoid robots for workplaces and homes by 2030, with a long-term goal of creating multifunctional humanoid robots by 2050 that can perform all human tasks and make independent decisions [1][4]. Group 1: Current Status of Humanoid Robotics in Japan - Despite rumors of Japan exiting the humanoid robot competition after Honda discontinued Asimo, the country's technological strength and research enthusiasm in this field have not diminished [4][6]. - Major Japanese institutions like Toyota Research Institute and Kawasaki Heavy Industries continue to hold patents and advance humanoid robot technology [6]. Group 2: Key Players and Developments - Toyota Research Institute (TRI) has been focusing on humanoid robotics since its establishment in 2015, collaborating with Boston Dynamics to enhance the Atlas robot's autonomous task handling capabilities [7][10]. - The collaboration with Boston Dynamics aims to integrate TRI's large behavior model into Atlas, allowing it to autonomously generate control signals based on various inputs [10][12]. - TMSUK, a representative company in service robots, has developed humanoid robots for various fields, including a dental training robot that simulates children's behavior for training purposes [13][15]. Group 3: Future Plans and Collaborations - TMSUK plans to develop a prototype humanoid robot for disaster response by the end of 2026 in collaboration with several institutions [19]. - Kawasaki Heavy Industries has iterated its Kaleido series of humanoid robots, with the latest models capable of complex tasks and enhanced human interaction features [34][36]. - Murata Manufacturing is also involved in humanoid robotics, with plans to start trials for domestically produced humanoid robots by March 2026 [33]. Group 4: Global Context and Competition - Other countries, such as South Korea, are also advancing in humanoid robotics, with plans to develop commercial humanoid robots by 2028, involving major tech companies [39][41]. - The global landscape for humanoid robotics remains competitive, with no standout companies achieving mass production yet, indicating that the industry is still in its early stages [41][42].

Core Insights - Beijing is positioning itself as a leader in future industries, focusing on sectors like 6G and embodied intelligence, aiming to become a global benchmark for digital economy by the end of the 14th Five-Year Plan [1] - The city has integrated future industries into its "2441" high-precision industrial system and has outlined a comprehensive policy framework to promote disruptive technologies [1][2] Group 1: Future Industry Development - Beijing has established a "2+N" spatial layout, with Haidian District focusing on general artificial intelligence and quantum information, while the Economic Development Zone is developing a high-level autonomous driving demonstration area [2] - The city is accelerating the creation of future industry pilot zones in Haidian and Changping Districts, aiming to integrate innovation, industry, finance, and talent [2] Group 2: Sector-Specific Focus - Key sectors include future information, health, manufacturing, energy, materials, and space, with specific districts assigned to lead in these areas [4][5] - The city is fostering advancements in hydrogen energy, new energy storage, and synthetic biology, among other fields, to drive technological innovation [2][5]

有人戏言，说美国硅谷科技公司中来自人工智能领域的人才，有一半都是国人。 今年6月份，Meta首席执行官马克·扎克伯格公布超级智能实验室时，列出了11位加入该计划的人工智能研究员，他们都是人工智能领域的大拿，扎克伯格的 目标，就是打造一台比人类大脑更强大的机器。 根据公开资料显示，扎克伯格组建的超级智能实验室中的11位成员，全部都是在其他国家接受教育的移民，而其中有七人，也就是超过一半都来自我国。 这就是今天的硅谷现状，嘴里说着要大国竞争，但实际上用的人很大一部分都来自我国。 为什么我国的人工智能人才，都喜欢往美国跑？ 尽管目前特朗普已经收紧了移民，美国鹰派对华情绪也日益高涨，但过去多年，在我国出生并接受教育的研究人员，一直都在美国顶尖人工智能实验室扮演 着重要角色。 早在2020年，致力于促进中美建设性关系的保尔森研究所就发布研究称，我国人工智能研究员约占全球顶尖人工智能人才的近三分之一，但这些人大多就职 于美国企业和高校。 卡内基国际和平基金会的一项新研究也表示，这些我国研究员中的绝大多数仍然在为美国机构工作。2019年曾经入选原研究的100位就职于美国高校或企业 的顶尖我国研究员中，如今仍然有高达87位在 ...

Core Insights - Acknowledging setbacks is the first step for Google to restart its AI journey, leading to a restructuring of its foundational architecture and a focus on multi-modal understanding as a core advantage [1][6] - The release of Gemini 3 marks a significant turnaround for Google, demonstrating its ability to not only catch up but also redefine its organizational methodology and technological path [4][8] Group 1: Acknowledgment of Challenges - Google’s AI chief openly admitted that the company had fallen behind, particularly in the wake of ChatGPT's rise, which shifted industry focus towards OpenAI [3][4] - The internal consensus shifted, recognizing that traditional long-term research alone could not keep pace with the rapid evolution of AI technology [5][6] Group 2: Multi-Modal Understanding - Multi-modal capabilities are essential for understanding the complexities of the real world, as they integrate text, images, audio, and video into a unified model [7][8] - Google’s approach involves restructuring at the architectural level to allow different modalities to be trained together, enhancing the model's ability to comprehend the world rather than just generating aesthetically pleasing outputs [7][8] Group 3: Organizational Restructuring - The transformation of Google’s organizational structure from a serial pipeline to a parallel system has significantly accelerated the development and deployment of Gemini [8][9] - This restructuring allows for real-time collaboration among product managers, engineering teams, and safety protocols, leading to a more cohesive and efficient development process [8][10] Group 4: Enhanced Usability and Functionality - The improvements in Gemini's user experience are attributed to a focus on usability, including enhanced instruction comprehension and internationalization capabilities [11][12] - The model's ability to execute tasks rather than merely respond to queries marks a shift towards more actionable intelligence [13][14] Group 5: Competitive Advantages - Google’s competitive edge lies not just in model capabilities but also in its robust infrastructure, including TPU, global data centers, and a mature security system [15][16] - The activation of this infrastructure has been pivotal in Google’s rapid recovery from being perceived as a laggard in the AI space [16] Group 6: Future Directions - The next phase of AI competition will focus on action-oriented intelligence rather than just conversational capabilities, with an emphasis on automating workflows and enhancing developer tools [17][18] - The distinction between dialogue models as products and action models as platforms highlights the greater commercial value of the latter [19] Group 7: Broader Implications - The real measure of progress is the application of models in real-world scenarios across various fields, indicating a shift towards practical utility in AI development [20][21] - The journey from research to product integration reflects a significant evolution in Google’s approach to AI, emphasizing the importance of user feedback and real-world applicability [44][59]

Core Insights - The AI industry is experiencing rapid changes, with major players like Google and Alibaba making significant advancements in AI models and chips, indicating a competitive landscape that is constantly evolving [1][2] - The emergence of new players like DeepSeek demonstrates that established companies are not guaranteed dominance, as the speed of technological iteration can disrupt traditional market leaders [1][2] - The shift from closed development to open collaboration in AI research is fostering a more equitable competitive environment, allowing for faster innovation and shared technological advancements [2][3] Group 1 - Major companies are launching new AI models and chips, with Google nearing a market valuation of $4 trillion and Alibaba aggressively entering the AI to C market [1] - The rapid pace of AI development is creating opportunities for new entrants, as seen with DeepSeek's rise, which challenges established players like Nvidia and ChatGPT [1][2] - The diverse needs across industries, such as banking and healthcare, highlight the importance of specialized solutions over general models, allowing smaller teams to excel in niche markets [2] Group 2 - The competitive landscape is shifting towards a focus on technological advantages and execution efficiency, rather than traditional strengths like user base and funding [3] - The AI sector is characterized by a lack of permanent leaders, with new companies emerging as potential frontrunners based on their ability to adapt and innovate [3] - Investors are becoming more discerning, emphasizing the need for practical applications and scenario breakthroughs, which is leading to a more rational valuation system in the AI market [2]

Core Viewpoint - The AI industry is experiencing rapid changes, with no permanent leaders, as new players emerge and established companies face challenges from innovative technologies and competitors [1][3]. Group 1: Industry Dynamics - The AI landscape is characterized by intense competition, with major players like Google and Alibaba launching new models and technologies to capture market share [1][2]. - The emergence of new AI models, such as DeepSeek, demonstrates that established companies can be disrupted by innovative newcomers, highlighting the unpredictable nature of AI advancements [1][2]. - The decreasing cost of computing power and the availability of open-source code have leveled the playing field, allowing global participants to compete more equally [2]. Group 2: Technological Evolution - The rapid pace of technological iteration in AI means that traditional advantages, such as user base and financial strength, are becoming less reliable [3]. - Companies are shifting from closed development to open collaboration, which fosters a shared technological foundation and accelerates innovation across the industry [2]. - The diverse needs of various sectors, such as banking and healthcare, create opportunities for specialized teams to excel in niche markets, despite the heavy investments made by larger firms in general models [2]. Group 3: Investment Landscape - Investors are becoming more discerning, focusing on practical applications and scenario breakthroughs rather than just concepts, which encourages a more rational valuation system [2]. - The evolving investor attitude supports fair competition, allowing promising projects to receive necessary backing despite the competitive landscape [2].