最近，国内奢华酒店江湖又杀出一匹黑马城市。 据华美云数据显示，截至2025年底，湖州以14家奢华酒店的数量，首次超越深圳的11家，跻身全国奢华酒店城市排行榜第五位，仅次于上海、北京、成 都、杭州。 就这样，一个GDP刚破4400亿的长三角三线城市，奢华酒店数量超越了GDP已逼近4万亿的国际化大都市。 这份反差的背后，是两座城市截然不同的发展路径。 当湖州凭一己之力打破"一线城市=奢华酒店高地"的固有印象，未来国内高端住宿市场，真的会迎来文旅导向替代商务导向的全新格局吗？ 深圳真的"躺平"了？ 要看懂湖州的逆袭，首先要打破一个误区。 奢华酒店数量，并不是非要与城市GDP绑定。 《中国奢华酒店市场洞察报告》中指出，中国奢华酒店已从"比硬件、拼品牌"的同质化阶段，进入"以高净值人群需求为核心，以体验和创新驱动"的新周 期。 深圳与湖州的对比，本质上是两种城市发展逻辑、两种酒旅消费需求的碰撞。 深圳作为科创中心和商务枢纽，一直以来，这里的奢华酒店都带着浓厚的商务气息。它们扎堆在福田CBD、前海合作区还有深圳湾超级总部这些地方， 主要就是为了服务那些跨国企业的高管、出差的商务人士，以及各种高端会议的需求。 这些酒店基本 ...

01 春节将至，国内各地外国人浓度突然高了起来。 这两天，一位在成都成华区某中端连锁酒店工作的朋友在旅界社群里晒了张截图，是他所在酒店的春节订单构成。 他说，自己本来只是想感慨一下今年春节又要满房了，结果翻了翻订单才发现，今年春节期间，每天竟然差不多有三分之一是老外。 | | 日 日本国际2017-12-19 11:21:21 10:12 10-12 11:12 11:52 11:1 | ( ( ) = ) | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 日期 | 可售房数 | 出租房数 | 用相率 | 外籍客人 | 外籍占比 | 国内客人 | 国内战 | 平均房价(元) | | 2/15 | 453 | 410 | 90.5% | 123 | 30.0% | 287 | 70.0% | 438 | | 2/16 | 453 | 418 | 92.3% | 125 | 29.9% | 293 | 70.1% | 452 | | 2/17 | 453 | 425 | 93.8% | 149 | 35.1% | 276 ...

Core Insights - OpenAI has made significant advancements in AI technology with the release of GPT-5.3-Codex, which enhances programming capabilities and introduces a new framework for AI integration in enterprise workflows [2][3][31] Group 1: GPT-5.3-Codex Capabilities - GPT-5.3-Codex is OpenAI's most powerful programming model, improving reasoning speed by approximately 25% and capable of handling complex tasks with real-time user interaction [2][3] - The model has evolved from a programming assistant to a general-purpose agent, capable of autonomously designing and optimizing applications, such as games, and generating user-friendly web pages [3][6] - It supports the entire software development lifecycle, extending its capabilities to tasks like creating presentations, spreadsheets, and data analysis [6][15] Group 2: Codex App Server - OpenAI introduced the Codex App Server, a standardized communication protocol for integrating Codex across various platforms, enabling seamless interaction between AI agents and users [17][20] - The App Server utilizes a structured remote procedure call protocol (JSON-RPC) and supports bidirectional communication, enhancing the interaction complexity between users and AI agents [17][20] Group 3: Frontier Platform - OpenAI launched the Frontier platform to help enterprises deploy and manage AI agents effectively, addressing the "AI opportunity gap" where models are underutilized due to lack of context [23][28] - Frontier enables AI agents to understand business logic, operate real tools securely, continuously improve through practice, and maintain strict identity and permission controls [23][24][25][26] Group 4: Trusted Access for Cybersecurity - OpenAI introduced the "Trusted Access for Cyber" initiative to balance the deployment of AI in cybersecurity with the prevention of misuse, implementing a tiered trust strategy for user access [29][30] - The initiative includes a $10 million funding program to support teams demonstrating effective vulnerability remediation in open-source software and critical infrastructure [30] Group 5: Systematic Approach to AI Integration - OpenAI's recent releases reflect a systematic approach to AI integration, emphasizing the need for AI agents to work collaboratively like human employees, with a focus on governance and responsibility [31]

宗教场所是文旅景区非常重要的组成部分，许多著名景区都有宗教的加持。在旅游领域一直存在"偏心"的现象，即佛教景区的旅游吸引力常常大过道教景 区。 佛教有四大名山，五台山、普陀山、峨眉山、九华山，每一座都是堪称顶流的文旅景区。其中，峨眉山、九华山诞生了文旅上市公司峨眉山A、九华旅 游。普陀山和五台山屡屡传出拟上市计划，但因宗教文化界反对声音过大而取消。 道教四大名山，武当山、龙虎山、青城山、齐云山，其客流量较佛教名山差一个档次。上市方面，武当山、齐云山勉强算"半上市公司"。武当山上不去A 股，就去了新三板，新三板挂牌公司武当旅游，2024年武当旅游年营收仅1.8亿元。对比之下峨眉山A、九华旅游2024年营收分别为10亿元、7.6亿元。齐 云山和张家界百龙天梯、黄龙洞、凤凰古城游船等一起打包，注入到上市公司祥源文旅。 佛教除四大名山外，还有一批顶流文旅项目，嵩山少林寺、无锡灵山梵宫、杭州灵隐寺、北京雍和宫，乃至以佛教艺术为核心的龙门石窟、敦煌莫高窟。 而道教其他景区，只有近几年逐渐火热的老君山、三清山拿得出手。 佛道的信众基础不同 为什么道教景区干不过佛教景区？ 需要指出，道教景区和佛教景区并非完全泾渭分明的两大阵 ...

当谷歌的大模型 Gemini 3 在2025年末以惊人的多模态处理速度和极低的延迟震撼业界时，外界往往将目光聚焦于算法的精进。然而，真正的功臣正沉默 地跳动在谷歌数据中心的机架上——那就是他们潜研10年的 TPU (Tensor Processing Unit)。 长期以来，英伟达凭借其"通用而强大"的 GPU 统治了模型训练的黄金时代。但随着大模型走进规模化应用爆发期，算力逻辑正发生本质改变："训练为 王"的旧秩序正在瓦解，"推理为王"的新时代已经降临。 当专用架构的极致效率突破了通用架构的冗余局限，以 TPU 为代表的 ASIC 芯片正以不可阻挡之势，从英伟达手中接过主角的剧本，重塑全球AI算力的 权力版图。 成本为王，芯片变了 这些年，在海内外厂商的共同推动下，大模型和人工智能成为了几乎人尽皆知的热词。所谓大模型，其诞生有点像一个人的成长：先通过预训练"博览群 书"，在海量文本中学习语言结构和世界知识；再通过指令微调，学会如何按人类要求组织和表达回答；接着借助基于人类反馈的强化学习，对齐输出风 格与边界，使回答更符合人类偏好；最后经过压缩和工程优化部署到服务器上，在与用户交互时实时解析输入，并以逐词预测 ...

Group 1 - The core point of the article is that Mu Xi Integrated Circuit (Shanghai) Co., Ltd. has increased its registered capital from 360 million yuan to approximately 400 million yuan [1] - The company was established in September 2020 and operates in the fields of integrated circuit technology, electronic technology, communication technology, and computer software and hardware technology services [1] - The funding for the company comes from Shanghai Jiao Mai Enterprise Consulting Partnership (Limited Partnership) and Chen Weiliang among others [1]

到这个月的月底，许家印失去自由3年5个月。 但你能想到吗，身陷囹圄的许家印，仍有权每月支取约5万港元的费用。 这恐怕是2026年开年以来最为吊诡的一幕。尽管许教授从未提出过这样的申请。 清盘中的中国恒大诉请追索许家印、夏海钧等前高管违规所获薪资奖金以来，许家印委托了不止一位大 律师。香港的大律师很贵，这是周知的事实。虽然当下拖着诉讼费不给，但是，许家印对于律师费的支 付倒是十分爽快。 我们掌握的情况显示，一般律师费用单发出两个月以内，许家印方面就会完成费用结算。他从未拖欠过 律师费用。 这些钱从哪里来的？ 恒大极盛之年，5万港元这种小钱，在许家印那里恐怕连毛毛雨都算不上。但是，今时不同往日，如今 的许家印已经连120万港元的诉讼费都不能如期缴纳，还要劳动香港法庭兴师动众开庭审理，以"除非 令"威慑，催促许家印赶紧交钱。 2月3日，香港法庭签发针对许家印的判词，要求他在2月20日前向法庭缴纳诉讼费，否则将以"除非 令"剥夺他在日后诉讼中的抗辩权。如果从2月5日开始计算，留给许家印的时间，还有不到15天。 人们不禁好奇，届时许家印会以不交诉讼费的方式放弃自己的抗辩权么？ 即便是现在的许家印，也绝非是没钱。许教授到 ...

Core Insights - The article discusses how Zhengzhou has emerged as a significant hub for micro-short dramas, leveraging its unique resources and conditions to become the largest "vertical store" for this industry in China [2][11]. Industry Overview - Zhengzhou's micro-short drama market reached a scale of 3.85 billion yuan from January to August 2025, with over 100 new productions daily [5]. - The workforce in this sector surged from 6,000 in 2023 to nearly 40,000, with 70% being young individuals under 30 [7]. Production Capabilities - Zhengzhou has developed a complete industry chain for micro-short dramas, including script incubation, production, distribution, and copyright management [7]. - The city has transformed previously idle commercial spaces and factories into filming studios, with 15 professional filming bases covering over 160,000 square meters [9]. Cost Advantages - The low-cost space availability in Zhengzhou allows for quick and inexpensive modifications to create diverse filming environments, significantly reducing production costs compared to first-tier cities [11][12]. - The overall production cost for a 100-episode micro-short drama can be reduced to between 300,000 to 800,000 yuan, making it accessible for many small production teams [12]. Government Support - The local government has actively supported the micro-short drama industry through policies that include venue rewards and talent subsidies, aiming for a market scale of 10 billion yuan by 2027 [15]. Economic Impact - The micro-short drama industry has revitalized local economies, with increased consumption in surrounding areas such as restaurants and hotels, particularly in the aviation port area [17]. - The tourism sector has also benefited, with 15-18% of visitors in 2025 citing "following short dramas" as their reason for travel, contributing to a total tourism revenue of 220.6 billion yuan [29]. Cultural Influence - Micro-short dramas are reshaping Zhengzhou's cultural narrative and urban image, promoting local heritage sites and modern landmarks through storytelling [19][20]. - The city is transitioning from a traditional transportation hub to a vibrant cultural center, enhancing its identity beyond just being a populous province [19][30]. Replicability of Success - Other cities with idle resources may look to Zhengzhou's model for inspiration, focusing on flexible utilization of existing spaces and fostering an ecosystem that empowers content creators [20][22].

地铁客流量之后，快递业务量也成为观测城市活力的晴雨表。 那么，2025年，谁才是中国快递第一城？先说结论：如果从快递处理量来看，广州是中国快递第一城，金华（义乌）排名第二，深圳排名 第三。 2025年，广州的快递处理量达到了218.98亿件，相当于深圳的1.82倍、上海的1.9倍、北京的2.6倍，堪称"全国最忙"的城市。 如果从快递业务收入来看，上海是中国快递第一城，广州排名第二，深圳排名第三。2025年，上海快递业务收入达到2713.3亿元，断层式 领先，比广州、深圳、北京三城的总和还多854亿元。 01 快递处理量排名： 广州第一、金华第二、深圳第三 所谓快递处理量=快递业务量+快递投递量。简言之，就是指某地区在一定时间内寄出去的快递（快递业务量）和收到的快递（快递投递 量）的总和。 近日，国家邮政局公布2025年邮政行业运行情况，揭晓了各大城市的快递业务量排名，这个排名是很权威的。 以下就是2025年中国内地快递处理量排名前50位城市： | 排名 | | 快递处理量 | 排名 | 切尔司 | 快递处理量 | | --- | --- | --- | --- | --- | --- | | | | (万件) ...

Core Insights - The core argument of the articles is that the CRM software industry is undergoing a significant transformation driven by AI, with a shift towards an ecosystem competition rather than just product competition. This change is particularly evident in both the US and Chinese markets, where AI capabilities are becoming essential for CRM solutions [1][2]. Group 1: Market Trends - The CRM industry is experiencing a structural transformation driven by AI, characterized by five major trends: restructured growth logic, native AI implementation, upgraded outbound strategies, mainstream mergers and acquisitions, and AI as a core driver for domestic substitution [2]. - By the end of 2025, the US CRM market is expected to see a slowdown in growth, with Salesforce's revenue growth rate dropping to approximately 8.7% due to the maturity of traditional subscription models [3][5]. - In contrast, the Chinese CRM market is projected to reach a scale of about 65 billion yuan (approximately 9.5 billion USD) in 2025, with a growth rate of around 15%, primarily driven by domestic substitution [5]. Group 2: AI Integration and Ecosystem Development - AI has become the most critical variable in the CRM market, with significant adoption in SaaS applications. The competition is shifting from isolated functionalities to the overall system reconstruction and the speed of implementation [7][8]. - The integration of AI into existing CRM processes is essential for achieving reliable and scalable solutions. Companies are recognizing the importance of embedding AI deeply into their operational frameworks rather than relying solely on AI's probabilistic nature [7][8]. - The competition for AI CRM is expected to intensify in 2026, with nearly 80% of enterprises listing AI capabilities as a mandatory criterion for CRM procurement [8]. Group 3: Outbound Strategies and Global Expansion - Approximately 86% of surveyed enterprise software companies plan to include outbound strategies as a core part of their business, although most are still in the early stages of internationalization [10]. - The nature of outbound strategies is evolving from simple functional exports to the export of technical capabilities, industry experience, and AI capabilities, with AI becoming a significant growth engine in overseas markets [10][12]. - Companies are increasingly adopting a "follow strategy," prioritizing service for internationalizing Chinese clients, which helps mitigate market risks and facilitates product internationalization [12]. Group 4: Mergers and Acquisitions - Mergers and acquisitions have become the primary path for expansion and exit in the global B2B software market, with nearly 70% of transactions occurring in the second half of the year [13][14]. - The focus of acquisitions is shifting towards technology support, data assets, and enterprise security, highlighting the necessity of building a compliant and reliable operational foundation in the context of AI [13][14]. - The competitive landscape is evolving into an ecosystem battle, where companies lacking systemic support for their technologies are at risk of being overshadowed by those with robust ecosystems [13][14]. Group 5: Domestic Substitution and AI as a Driver - AI is becoming a core driver for domestic substitution in the Chinese enterprise software market, with predictions indicating that the domestic CRM replacement rate will exceed 65% by the end of 2025 [15][17]. - The demand for AI capabilities is rapidly increasing as companies seek to integrate AI into their operations, particularly in light of limitations on the use of foreign AI models in China [17][18]. - The integration of AI into domestic CRM solutions is enhancing their usability and effectiveness, with significant improvements in data management and operational efficiency being reported [18][19].