12月25日，《广州市扶持游戏电竞产业发展的十八条措施》（以下简称《措施》）正式发布。这是广州 首个扶持游戏电竞产业发展的专项政策，旨在以"真金白银"的投入推动产业高质量发展，力争到2030年 将广州建设成为全球游戏电竞行业最具影响力的城市之一。 对在游戏科技领域取得显著突破的优质项目，给予最高不超过300万元的一次性扶持奖励； 鼓励原创精品研发，对重点扶持的游戏选题，给予每款游戏的研发单位最高不超过200万元的事前一次 性补助，对重点扶持的中小型游戏（含小程序游戏）选题，给予每款游戏的研发单位最高不超过20万元 的事前一次性补助； 激励产品运营，对上线1年以上3年以下（均含本数）、具有强大文化传播力和社会影响力的优秀游戏产 品，按照营业收入分成给予游戏运营单位最高不超过500万元的事后一次性补助； 推动游戏出海，对在海外发行、影响力强的优秀游戏产品，按照每款游戏产品年度实际结汇金额，给予 最高不超过30万元的事后一次性补助。 在电竞领域，《措施》支持引进或培育顶级赛事，给予每项赛事主办单位或承办单位最高不超过500万 元的事后一次性补助；电竞赛事联盟根据年度赛事总投入，最高可获200万元事后一次性补助。 政 ...

2025年12月，在腾讯科技HiTechDay上，以《模型再进化：2025，智能重新定义世界》为主题的圆桌论坛，正是围绕大模型进化的深度、维度、效率三条 线索展开。 华中师范大学人工智能教育学部助理教授熊宇轩为嘉宾主持，三位嘉宾北京智源人工智能研究院院长王仲远、面壁智能联合创始人、首席科学家刘知远、 峰瑞资本投资合伙人陈石分别从各自的领域，解读2025对于大模型进化的深入观察。 王仲远指出，大模型的进化正在经历"从Learning from Text到Learning from Video"的质变。视频数据中蕴含了丰富的时空信息与动态交互线索，为模型学 习物理世界动态演变规律提供了关键的数据来源，同时也是当前最容易规模化获取的一类多模态数据，是AI"从数字世界迈向物理世界"的关键桥梁，也为 具身智能（Embodied AI）的爆发提供了构建"世界模型"的底座。 刘知远提出的"密度法则"（Densing Law）认为，如同芯片摩尔定律，AI的未来在于不断提升单位参数内的"智能密度"。他大胆预言，未来的算力格局将 是"云端负责规划，端侧负责做事（执行）"，到2030年，我们甚至有望在端侧设备上承载GPT-5级别的 ...

Core Viewpoint - Jiangnan Chemical plans to acquire 100% of Xi'an Qinghua Civil Explosives Co., Ltd. for approximately 645 million yuan, aiming to enhance its core business and resolve industry competition issues with its controlling shareholder, Northern Special Energy Group [1][6][8]. Group 1: Acquisition Details - The acquisition price of 645 million yuan represents a premium of approximately 234.60% over the book net asset value of 193 million yuan as of June 2025 [6][10]. - The target company, Qinghua Civil Explosives, is recognized as one of the most comprehensive industrial detonator manufacturers in China and was awarded the national "specialized, refined, distinctive, and innovative" small giant enterprise title in October 2025 [6][10]. - This transaction is classified as a related party transaction, as Northern Special Energy Group holds a 21.74% stake in Jiangnan Chemical [6][7]. Group 2: Financial Performance - From 2020 to 2024, Jiangnan Chemical's average annual profit was approximately 730 million yuan, with a net profit of 664 million yuan achieved in the first three quarters of 2025 [4][12]. - Despite the acquisition activities, the company's financial health remains stable, with a debt-to-asset ratio of 39.93% as of September 2025 [5]. - The company's revenue grew from 3.919 billion yuan in 2020 to 9.481 billion yuan in 2024, nearing the 10 billion yuan mark [11]. Group 3: Business Strategy and Growth - Jiangnan Chemical has been actively pursuing external acquisitions to enhance its industry layout, including multiple acquisitions from its controlling shareholder [9][10]. - The company has expanded its production capacity to 777,500 tons of industrial explosives, positioning itself among the top tier in the industry [10]. - In addition to its core explosives business, Jiangnan Chemical is also investing in the renewable energy sector, with a cumulative installed capacity of approximately 1.06 million kilowatts in wind and solar power by June 2025 [2][10].

以下文章来源于中欧商业评论 ，作者维舟 中欧商业评论 . 中欧商业评论创办于2008年，隶属中欧出版集团，是一家深耕主流商业可持续发展，陪伴大型企业经营 管理者长期进步的专业内容服务厂牌。 来源丨中欧商业评论（ID： ceibs-cbr ） 作者丨 维舟 图源丨Midjourney 多少年来，国内许多省份都是省会"一城独大"的格局，不断做大做强省会，但物极必反，现在一种相 反的声音也越来越响：偌大一省只有"一个中心"是不行的，还得有"多个支点"。 不久前，国务院发布《关于推动城市高质量发展的意见》，以红头文件形式明确提到"推动有条件的 省份培育发展省域副中心城市"。最早的信号可能是2020年《求是》杂志在《国家中长期经济社会发 展战略若干重大问题》一文中提到的，"中西部有条件的省区，要有意识地培育多个中心城市，避 免'一市独大'的弊端"；《2022年新型城镇化和城乡融合发展重点任务》也专门提到，有必要严控省 会城市规模扩张；去年，"新时代推动西部大开发"座谈会上，提出的建议之一，就是"发展壮大一批 省域副中心城市"。 在那之后，各省都开始注重培育1-3个省域副中心城市，目前已有15个省区确立 了20多个"副中 ...

01 省会"一城独大"的另一面 要解决这个问题，可不是发个文件那么简单，毕竟"冰冻三尺，非一日之寒"，其中盘根错节的症结，都是长年累月积攒下来的，要改变也绝非易事。 正如研究区域经济发展的学者张耀军曾指出的，改革开放这四十多年来来，"强省会"一直是中国区域发展的普遍特点，除了东部沿海少数省份外，绝大部 分地区都得靠强省会为龙头来拉动经济发展。 在那些经济发达省份，城市经济格局都是"双核驱动"的，政治中心与经济中心分离，典型的如：广东的广州和深圳、江苏的南京和苏州、浙江的杭州与宁 波、山东的济南与青岛，再加上辽宁的沈阳与大连，福建更是"三核驱动"（福州、泉州、厦门并驾齐驱）。这使省内的资源分布更为均衡，也带动不同区 域协同发展，走向共同富裕。事实上，在所有省份中，福建和浙江的省内各地人均GDP差距是最小的。 然而，在中西部省份却是另一番模样：首位度最高的银川、长春都贡献了本省区一半以上的经济重量，吸纳了省内大部分资源，呈现出一骑绝尘的绝对优 势地位。这种"举全省之力发展省会"的强省会战略，本意是想让省会辐射带动全省发展，但在现实中，却往往是省会"一城独大"，使省会与其它地方的差 距进一步拉开，区域发展因此失衡。 ...

Core Insights - The competition landscape among non-provincial capital cities in Central and Western China is becoming clearer, with cities like Yulin, Yichang, and Luoyang emerging as leaders in GDP performance [1][4] - The construction of provincial sub-center cities is gaining new momentum, as highlighted by recent government policies aimed at fostering multiple center cities to avoid the pitfalls of a single dominant city [2][10] Economic Performance - Yulin leads the pack with a GDP of 565.41 billion, followed by Yichang at 455.33 billion and Luoyang at 445.49 billion, indicating a significant gap between Yulin and its competitors [1][4] - The GDP growth rates for Yichang, Luoyang, and other cities like Ordos and Xiangyang are showing varied performance, with Yichang and Luoyang achieving growth rates of 7.0% and 5.8% respectively [4][5] Provincial Sub-Center Cities - At least 28 cities in Central and Western China have been designated as provincial sub-centers, contributing to local economic growth alongside provincial capitals [2][3] - The rise of sub-center cities is characterized by a shift in economic focus from resource-based to innovation-driven economies, with cities like Yichang and Luoyang showing strong industrial growth [6][7] Future Outlook - The recent government directives suggest a strategic shift towards enhancing the role of provincial sub-center cities, which may lead to increased resource allocation and support for these cities [10][11] - The potential for a "dual-core" development model is emerging, where sub-center cities like Yulin, Yichang, and others aim to achieve trillion-yuan GDP targets, thereby supporting regional economic diversification [10][11]

Core Insights - The mainstream narrative around artificial intelligence (AI) is undergoing a profound shift towards a new paradigm based on large models and agents as the core of interaction, accelerating penetration into various industries [2][4] - The AI industry is experiencing a valuation reconstruction, with significant interest from global investors in infrastructure-related stocks such as artificial intelligence, semiconductors, and computing chips [4][10] - The AI revolution is characterized as an "intelligent revolution," where AI evolves beyond being a mere tool to becoming intelligence itself, necessitating the emergence of "AI architects" across industries [5][7] Industry Trends - The demand for intelligent upgrades in sectors like finance, healthcare, manufacturing, and smart cities is surging due to the deep integration of large models [4][9] - The concept of "agent economy" is emerging, where economic activities will be coordinated and executed by agents, redefining labor markets and organizational structures [9][10] - The AI industry is expected to form a "dual-core" driving pattern, with the coexistence of closed-source and open-source large models, and the competition between the US and China as key players [10][11] Investment Opportunities - The AI sector is seen as a fertile ground for nurturing world-class companies, particularly in manufacturing and finance, with a focus on long-term investment strategies [8][9] - The construction of advanced computing infrastructure is critical for the development of artificial general intelligence (AGI), with a focus on creating more efficient and powerful computing centers [13][15] - Companies are encouraged to focus on vertical scenarios to create sustainable business models and address high-frequency pain points in specific industries [20][22] Technological Developments - The integration of AI into various sectors is leading to a transformation from human-centered services to agent-centered services, enhancing decision-making capabilities [19][20] - AI applications are expected to evolve from being productivity tools to becoming the core of productivity itself, emphasizing results over processes [19][22] - The AI hardware market is anticipated to thrive by combining agents with hardware and vertical scenarios, enhancing user experience through context-aware interactions [22][23] Educational Innovations - AI is poised to address traditional education challenges by providing personalized learning experiences and focusing on students' holistic development [25][29] - The integration of AI in education aims to overcome limitations such as teacher scarcity and uniform learning speeds, promoting tailored educational solutions [25][29]