Core Viewpoint - The AI sector, particularly the "AI Four Strong" companies, is experiencing a resurgence as they pivot towards Deep Research and AI Agents to compete with larger firms and demonstrate their value to investors [1][3][21]. Group 1: AI Four Strong's Strategy - The AI Four Strong have launched their own Deep Research products, aiming to regain market presence after a period of low activity [2][9]. - These companies are focusing on vertical integration and delivering value through Deep Research and AI Agents, which are seen as safer positions amid competition from larger firms [3][4]. - The introduction of AI Agents is not only a strategy to re-enter the market but also a way to create monetizable opportunities, with reports indicating significant user upgrades to premium services [5][21]. Group 2: Market Dynamics and Competition - The AI landscape has shifted with the emergence of Deep Research as a new benchmark, prompting the AI Four Strong to innovate rapidly [8][17]. - The competition has intensified, with major players like Tencent and Alibaba also entering the fray, leading to a reassessment of strategies among the AI Four Strong [17][20]. - The AI Four Strong are now prioritizing technological advancements over user growth, reflecting a strategic shift in response to market pressures [20][21]. Group 3: Product Development and User Engagement - The AI Four Strong are adopting different approaches to product development, with some focusing on user-friendly interfaces while others emphasize high user interaction [12][13]. - Recent model releases, such as MiniMax's M1 and Kimi's K2, showcase significant advancements in capabilities, including increased parameter counts and improved efficiency [15][23]. - The need for AI Agents to deliver quantifiable value to clients is critical, as demonstrated by successful case studies that highlight efficiency improvements and cost reductions [27][28]. Group 4: Financial Outlook and Investment - The AI Four Strong are beginning to attract positive attention from investors, with reports of significant funding rounds and IPO plans [23][24]. - The financial viability of AI Agents is under scrutiny, as the costs associated with their use can be substantial, necessitating a focus on creating clear value propositions for clients [30][31]. - The overall market for AI Agents is still developing, with indications that achieving product-market fit remains a challenge for many companies in this space [31][32].

然而，无论发生什么样的新变化，出现什么样的新资产，直到现在，加密货币市场仍然几乎还是比特币的独角戏。直到2017年3月，比特币仍然占据加密 货币总市值的95%，中间几经波折，到2025年6月的当下，仍有65%。而加密货币总市值总额已经增长了160倍。 如果都是石缝中蹦出的猴子，是什么导致了比特币和其他加密货币的"人猿相揖别"？为什么比特币成为了一种意识形态，而其他加密货币没有？从诞生到 成长，比特币到底有哪些独一无二的特质，使得其能够无视周期，持续增长？ 一、纯洁的受孕 一般意义上的新事物诞生，不外乎两种来源：学术研究和企业创新。但在学术和产业之外，中本聪为比特币建设了第三条道路。他的白皮书发布时，没有 接受学界的同行评审，也不是一个企业的实验室中研究出的新产品。或许，从诞生之初，中本聪就非常先见地意识到无论哪种科层制都无法容纳下他激进 的思想。 2025年1月，特朗普币横空出世。相比 2009 年 1 月，中本聪把 "Chancellor on brink of second bailout for banks" 写进比特币创世区块时的无人知晓，特朗普 币如现场直播一般把加密货币领域的一个机制展示在大众面前 ...

Core Viewpoint - The rapid development of China's new energy vehicle (NEV) industry is a reflection of dynamic industrial governance, with government policies playing a crucial role in various stages of development [1][5][27]. Group 1: Industry Development Stages - In the new technology exploration stage, the central government broke the inertia of traditional fuel vehicle manufacturers by implementing major special projects to promote innovation and avoid past mistakes of lacking core technologies [1][7]. - During the industrialization breakthrough stage, the government adjusted entry restrictions to encourage social capital participation, leading to a surge of internet companies entering the NEV sector and revitalizing market dynamics [2][15]. - The current shift towards software-driven vehicles necessitates further adjustments in industrial policies, as the industry transitions into the era of "software-defined cars" [3][24]. Group 2: Policy Impact and Market Dynamics - The introduction of policies has significantly altered the competitive landscape, with traditional automakers and new entrants vying for market share, leading to a vibrant competition in the NEV sector [19][20]. - The government’s initial focus on creating a policy-driven market has evolved into a more competitive environment, with the gradual withdrawal of subsidies and the introduction of market-driven mechanisms [25][26]. - The NEV market has seen a dramatic increase in production and sales, with a reported growth of over 300% in production and sales in 2015, highlighting the effectiveness of government policies in stimulating market demand [18][21]. Group 3: Challenges and Future Directions - The NEV industry faces challenges such as local protectionism and fraudulent subsidy claims, which have prompted the government to tighten subsidy policies and encourage a more competitive market environment [21][22]. - As the industry moves towards a software-driven future, the integration of ICT companies into the NEV sector is expected to reshape production and operational models, enhancing competitiveness [24][28]. - The potential impact of international policies, such as those from the EU aimed at reducing the market share of Chinese brands, poses new challenges for the NEV export market [28].

Group 1 - The core idea of the discussion revolves around the evolution of AI, highlighting two main paradigms: "symbolism" which focuses on logical reasoning, and "connectionism" which emphasizes learning from neural connections [1][2] - The speaker, Geoffrey Hinton, discusses the development of a small model in 1985 that combined these two theories, predicting the next word based on features rather than storing complete sentences [3][4] - The advancement of large language models, such as Google's Transformer and OpenAI's GPT, is noted, which utilize multi-dimensional features of words to generate and understand language [6][10] Group 2 - The discussion emphasizes the differences between human knowledge transmission and AI knowledge replication, with AI systems being able to copy and share knowledge at a much faster rate [9][13] - The concept of "knowledge distillation" is introduced, where knowledge from large models is transferred to smaller models, akin to a teacher-student relationship [16][17] - The potential for AI to surpass human intelligence is acknowledged, with concerns about control and the implications of highly intelligent AI systems [18][19] Group 3 - The need for global cooperation in AI safety is highlighted, suggesting the establishment of an international research network focused on training AI for beneficial purposes [20][21] - The second speaker, Yan Junjie, discusses the democratization of AI, emphasizing its role as a creative source and its integration into various fields, enhancing individual capabilities [24][25] - The observation that AI is increasingly being used in diverse applications, from ancient text analysis to astronomy, showcases its expanding utility [26][30] Group 4 - The belief that AI will not be monopolized by a few organizations is presented, with the argument that different models will emerge based on varying goals and values [32][33] - The rise of multi-agent systems and open-source models is noted, indicating a trend towards a more inclusive AI development landscape [34][35] - The discussion concludes with the assertion that AI will become more accessible and affordable, with a focus on the importance of collaborative efforts in achieving advancements in artificial general intelligence (AGI) [40]

"垂直Agent的机会，比垂直模型的机会要大很多。但关键点在于，要想明白用垂直Agent解决什么行业问题，从问题出发做上下文工程，并且做减法。"阿里 副总裁、阿里国际AI Business负责人张凯夫（花名：凯夫）对虎嗅表示。 虎嗅独家获悉，阿里国际内部在2024年把AIGC作为关键方向后，于2025年开始把焦点向Agent转移，其中包括可以进一步降本增效的电商工作流Agent。目 前，阿里国际内的AI布局包括了多模态模型Ovis、超过60种场景的AI应用以及正在推进中的Agent工具。 阿里副总裁、阿里国际AI Business负责人张凯夫 AI对阿里国际的业务影响是明显的。以阿里国际基于通义大模型为基座强化训练出的Ovis模型为例，2024年四季度该模型日均调用量超过1亿次，而到了 2025年上半年，这一数据已经超过10亿次。而在成本和收入环节，阿里国际相关的AI Agent已经让退款成本同比下降15%，广告投放ROI同比提升5%。据 悉，目前阿里国际AI提供的SEO占到了整体SEO的近4成。在今年的世界人工智能大会上，阿里国际的AI解决方案获得了大会的卓越人工智能引领者（Super AI Leader， ...

Core Insights - The article highlights the growing trend of outdoor extreme sports among the middle class, moving away from traditional urban activities like marathons to more adventurous options like obstacle races and trail running [2][3][4] Group 1: Emerging Sports Trends - The Spartan Race has gained significant popularity, with nearly 5,000 participants in the Beijing event alone, showcasing a shift towards more rugged and challenging outdoor activities [3][4] - The rise of trail running is evident, with the number of events increasing from 65 to 505 in a decade, indicating a growing interest in this sport among the middle class [7][10] - Ironman triathlons are also becoming more popular, with early bird registration for events selling out in minutes, reflecting the increasing demand for such extreme sports [10][11] Group 2: Participant Demographics and Motivations - Participants in these events often have a fitness background, with many being amateur athletes or fitness enthusiasts, indicating a shift in the demographic engaging in these sports [4][28] - The desire for personal growth and social connection drives many middle-class individuals to participate in these extreme sports, as they seek to break free from the monotony of urban life [12][34] - The social aspect of these sports is significant, with participants often forming communities and networks around shared interests in outdoor activities [35][36] Group 3: Economic Considerations - The costs associated with outdoor sports, including registration fees and equipment, are generally higher than traditional urban sports, reflecting the economic barriers to entry [14][15] - Participants often invest significantly in gear and training, with some spending over 10,000 yuan on equipment and training for triathlons [16][29] - The financial commitment is seen as a reflection of the value placed on these experiences, with many participants viewing them as a form of personal investment [30][31] Group 4: Challenges and Preparation - The physical demands of these sports require participants to undergo rigorous training, with many needing to prepare for months before competing [18][22] - Newcomers often face challenges in adapting to the physical and technical requirements of these sports, highlighting the need for proper preparation and knowledge [19][25] - The article emphasizes the importance of gradual progression and understanding the specific demands of each sport to ensure safety and enjoyment [19][22]

Group 1 - The article discusses the educational advantages of Hong Kong compared to Shanghai, highlighting that Hong Kong offers a more continuous education system without the pressure of early selection processes like the 中考 in mainland China [8][14] - It notes that in 2025, approximately 15% of students from Shanghai are expected to enter 985/211 universities, while the proportion for Hong Kong's top eight universities is around 30%, suggesting a higher acceptance rate in Hong Kong [7][11] - The article emphasizes the flexibility in Hong Kong's education system, allowing students to transfer schools and pursue better opportunities, which is less common in Shanghai [8][12] Group 2 - The author points out that while Hong Kong's education system may be less rigorous than Shanghai's, it places a greater emphasis on practical application and overall development across subjects [9] - It is mentioned that teachers in Hong Kong maintain a more neutral stance regarding gifts from parents, contrasting with the practices observed in Shanghai, which can create a more equitable environment [10] - The article concludes that while there are educational advantages in Hong Kong, moving solely for educational reasons may not be advisable unless accompanied by career opportunities [14][15]

美国的驻外大使分为两类：一类是外交官出身的"职业大使"，另一类是跟总统关系密切的"政治大使"。 早些年间，"职业大使"的占比要明显高于"政治大使"，后来随着总统大选消耗的人力物力财力越来越多，驻外大使逐渐 成为获胜一方回馈重要助选者的一种酬劳性岗位，于是"政治大使"的比例越来越高。 典型例子如民主党大使专业户卡罗琳·肯尼迪——肯尼迪总统的女儿。 根据美国的人事任命流程，新任大使须经总统提名、参议院听证会批准后才可就任，因此换届往往会出现数个月的空 缺。 这里面门道就来了，新总统先提名哪些大使、后提名哪些大使，可以一定程度上反映其外交侧重方向。 2012年美国大选的激烈关头，卡罗琳·肯尼迪力挺奥巴马，称"奥巴马像我的父亲"，当选后奥巴马立即提名其担任驻日本 大使。 到2020年拜登和特朗普唇枪舌剑的时候，卡罗琳·肯尼迪再度出来助选，称"我在参议院实习时就是拜登的铁粉"，当选后 拜登提名她出任驻澳大利亚大使。 政治是有规矩的，欠人情必须还，当新总统在舞台中央风光无限之时，切记要雨露均沾到每一个选举桩脚，这样才能保 持队伍的战斗力。 按照原先的规矩，每当总统换届，外交官出身的"职业大使"是不需要更换的，新总统撤换的 ...

Group 1 - The core idea presented is that in the AI era, effective learning requires clarity on what not to learn before pursuing new knowledge [3][4][5] - The importance of setting clear life goals and aligning learning objectives with those goals is emphasized [5][6] - Many individuals tend to learn haphazardly without a clear direction, leading to wasted time and effort [7][8] Group 2 - A recommended approach is to start real projects and learn through practical experience rather than following tutorials from start to finish [7][11][16] - The experience of using AI tools in real projects has proven to be more beneficial than theoretical learning [15][16] - Learning in the context of actual work allows for immediate application of skills, enhancing retention and relevance [17][22] Group 3 - Strategies for overcoming procrastination include starting with small, manageable tasks to build momentum [18][19] - Sharing progress publicly, such as through writing or teaching, can reinforce understanding and foster community engagement [20][21] - The overall methodology encourages proactive, goal-oriented learning that evolves through practice and iteration [22]

一位优雅的女士靠在沙发边，侧身翻看着一叠图纸，光线从客厅落地窗斜斜照进来，勾出她额角几缕银白的发。茶几上放着几页潦草的草图，是她先生 ——贝聿铭——昨夜未眠画下的修改稿。 这是1980年代一个普通的清晨，在贝氏家中，这样的场景早已习以为常。 她不是设计师，却参与了无数作品的诞生；她几乎不出现在镜头里，也从未在领奖台上站过一秒，但在贝聿铭之后的漫长岁月里，这位温和又坚定的女 性，是他人生最坚实的构造支柱。 她叫卢爱玲，原名卢淑华，很多人并不熟悉她的名字。 不久前，我访谈了贝聿铭的儿子贝礼中（父亲是贝聿铭，母亲被忽略）。他在访谈中提起自己的母亲："我母亲是一个被遗忘的人，但她对父亲的成功至 关重要。"他把"至关重要"这个词的英文重复了两遍。 在那一瞬间，我意识到，在那段横跨世纪、波澜壮阔的建筑传奇背后，还藏着另一个长期被忽视的名字。 然而，受限于篇幅，卢爱玲的故事在专访中未能展开太多。 于是有了这篇文章。我们试图从她走入公众视野的零星记录中，重新拼起她的人生剪影：出身于广州望族，是卫斯理学院的高材生、哈佛建筑系研究生， 亦是那个在建筑传奇背后默默撑起一片天的"无名英雄"。 无论是在婚姻起点的并肩求学，还是在建筑困 ...