Group 1 - The article emphasizes the importance of not making impulsive decisions before a date, particularly regarding footwear choices, as it can lead to embarrassing situations [1] - It humorously illustrates the consequences of wearing old shoes that may fall apart, leading to both physical and social discomfort [1] Group 2 - The article includes various humorous anecdotes and comments from readers, reflecting on personal experiences related to the main theme of the article [6][9][12] - It captures the essence of relatable life experiences, showcasing how small mishaps can lead to larger reflections on confidence and social interactions [17][19][21]

Core Insights - Huang Renxun emphasizes the importance of AI as the greatest "technological equalizer," suggesting that in the future, everyone will be a programmer, artist, or writer [21][22][23] - The allocation of the scarce H100 chips is based on a simple principle: first come, first served, with a smooth process for partners to plan ahead [28][25] - Huang Renxun takes pride in personally reviewing employee compensation and claims to have created more billionaires among executives than any other CEO [6][8][45] Group 1 - Huang Renxun revealed that NVIDIA has scrapped $50 billion worth of graphics cards, indicating the high demand for chips from tech giants like Zuckerberg and Musk [4][26] - The company is fully embracing AI across all levels, with employees being liberated from mundane tasks to pursue greater creativity, ultimately leading to growth and job creation [20][18] - Huang Renxun believes that the future will require AI as a co-pilot for programmers, making traditional coding methods obsolete [24][21] Group 2 - The H100 chip's value remains high, with a residual value of 75-80% after one year, thanks to the open CUDA platform that enhances performance [33][34] - Huang Renxun agrees with Musk's insight that the future will require 50 million H100-level computing chips, marking the beginning of a multi-trillion-dollar infrastructure wave [35][37] - The emergence of efficient open-source models like DeepSeek from China is seen as a victory for the U.S. tech stack, reinforcing its global standard [40][41] Group 3 - Huang Renxun acknowledges the significant compensation for top AI researchers, asserting that it is reasonable given the value they create [8][44] - He confirms his deep involvement in employee compensation, using machine learning to assist in the process, and states that he always increases salary expenditures [5][47] - The trend of small, elite teams driving innovation is highlighted, with companies like OpenAI and DeepSeek operating with around 150 top talents [9][46]

Core Viewpoint - The article discusses the resurgence of the "996" work culture in Silicon Valley, particularly within the AI startup sector, highlighting a shift from work-life balance to high-intensity work environments driven by competition and capital pressure [1][2]. Group 1: Emergence of 996 Work Culture - The "996" work schedule, which entails working from 9 AM to 9 PM six days a week, is becoming increasingly common in U.S. startups, especially in the AI field, as founders believe that intense effort is necessary to succeed in the technology race [1][2]. - Many startup CEOs are now asking potential hires if they are willing to accept a 996 work schedule during the interview process, making it a de facto requirement for some positions [2][3]. Group 2: Company Practices and Employee Responses - For instance, the AI startup Rilla explicitly states in its job postings that candidates uninterested in working over 70 hours a week should not apply, reflecting a culture where nearly all employees adhere to the 996 schedule [3]. - Some companies are adopting a "volunteer" approach, offering higher salaries and equity to those willing to work 996 hours, as seen in the remote healthcare company Fella & Delilah, where about 10% of employees opted for this arrangement [4]. Group 3: Perspectives on Work Intensity - The CEO of Sotira acknowledges that the 996 work culture is an open "unwritten rule" in the Bay Area startup scene, particularly during the initial years of a startup, although she notes that such demands should not be placed on regular employees [5]. - The debate over extended work hours is not limited to Silicon Valley; globally, there are discussions about whether more extreme work schedules, such as a "007" (working seven days a week), are necessary for building billion-dollar companies [6]. Group 4: Historical Context and Legal Considerations - Some individuals argue that the 996 culture has been prevalent in Silicon Valley for years, with many employees accepting high workloads in exchange for equity in startups, while others express concerns about the health implications of such work demands [7]. - There are warnings from industry experts that many companies enforcing 996 schedules may be violating labor laws by failing to classify positions correctly and not providing overtime pay, highlighting the legal risks associated with this work culture [7].

Core Viewpoint - The article highlights persistent issues in the domestic telecommunications industry, including opaque pricing, complex packages, and customer service challenges, which undermine user trust and satisfaction [1][6][8]. Group 1: Issues in the Telecommunications Industry - Users face non-transparent pricing, often encountering unexpected charges or automatic upgrades without clear communication [1]. - The variety of packages offered by operators is overwhelming, with complex names and terms that are difficult for many users, especially the elderly, to understand [2]. - Bundling of services often leads to hidden fees, with promotions like "free upgrades" frequently tied to automatic renewal clauses [3]. - Users experience difficulties when attempting to unsubscribe from packages, facing complicated processes and potential penalties [4]. - Operators sometimes cancel packages unilaterally without notifying users, forcing them to switch to less favorable options [5]. - Complaints about operators' practices, such as false advertising and unclear fees, have surged on various platforms, indicating a significant trust deficit [6]. Group 2: Regulatory Response and Industry Measures - Regulatory bodies have acknowledged the issues related to operators' charging practices and have called for reforms [9]. - Major telecom operators have pledged to address these service pain points, committing to transparency and responsiveness to customer concerns [10][11]. - China Mobile has introduced ten service commitments aimed at improving transparency and customer service, including clear pricing and proactive notifications [12][13][14]. - China Unicom announced sixteen measures to simplify and clarify its pricing structure, ensuring better communication with users [15]. - China Telecom has implemented nine measures to standardize service processes and improve the ease of unsubscribing from services [16]. - As of May, the total number of mobile phone users in China reached 1.807 billion, indicating that improvements in service will have widespread implications [17]. Group 3: User Expectations and Rights - While operators have made commitments to improve services, the effectiveness of these measures remains to be seen, with users expressing hope for genuine change rather than empty promises [18]. - In the mobile internet era, telecommunications services are essential, and operators must prioritize user rights to remain competitive [19].

Core Viewpoint - Apple's ambitious AI plans have faced significant setbacks, leading to the departure of key talent and delays in product launches, particularly the "Apple version of ChatGPT" which has been postponed to 2026 [2][4][5]. Group 1: Team Dynamics and Leadership Conflicts - The Apple AI team has experienced a major upheaval, with key figures leaving and the core team disbanding, primarily due to internal conflicts between the foundational model team and the software product team led by Craig Federighi [4][10][12]. - The foundational model team, led by former DeepMind expert Pang Ruoming, aimed to develop a general intelligence AI, while Federighi's team focused on practical applications, leading to a clash of visions [10][12][24]. - The decision to delay the release of AI features and the new Siri has caused frustration and confusion within the foundational model team, resulting in a loss of morale [14][31][34]. Group 2: Talent Exodus and Financial Incentives - Pang Ruoming's departure to Meta, with a reported compensation of up to $200 million over four years, has triggered a wave of resignations from the foundational model team, with many seeking opportunities at competitors like OpenAI and Anthropic [17][18][22]. - Apple's leadership has begun to reassess its compensation structure in an attempt to retain talent, a rare move for a company that has traditionally relied on its brand to attract employees [22]. - The loss of Pang, who was seen as a protective figure for the team, has led to a significant decline in team morale and cohesion [26][50]. Group 3: Strategic Missteps and Market Position - Apple's AI strategy has been criticized for lacking direction, with unclear goals regarding whether to compete directly with ChatGPT or pursue alternative paths [47]. - Despite having developed large language models prior to the rise of ChatGPT, Apple failed to respond effectively to the competitive landscape, resulting in missed opportunities [40][42]. - The foundational model team had made significant progress, including the development of a prototype capable of multi-turn dialogue, but was met with unexpected delays and a lack of communication from upper management [28][31][34].

Group 1 - The article discusses the absurdity of tasks assigned by leadership, highlighting the disconnect between expectations and reality in the workplace [1] - It emphasizes the concept of "paying first and using later" in the context of employment, where employees often have to cover expenses before receiving their salaries [9][10] - The notion of a trial period being akin to a "seven-day no-reason return policy" is presented, suggesting that employees feel like commodities in the job market [9] Group 2 - The article reflects on the emotional toll of work-related stress, indicating that negative experiences can linger and affect one's mental state throughout the day [49] - It touches on the importance of trust in the workplace, suggesting that repeated reminders from leadership may indicate a lack of confidence in employees [57] - The narrative includes humorous anecdotes about the challenges of working life, resonating with the experiences of many employees [5][12]

Core Viewpoint - A Canadian creator, Krish Shah, has developed an application called TrackWeight that transforms the Force Touch trackpad of MacBook Pro and MacBook Air into a digital weighing scale, capable of measuring small objects like coffee beans and remote controls with an accuracy of within 2 grams [2][4][8]. Group 1: Application Development - TrackWeight utilizes the pressure sensitivity feature of the Force Touch trackpad, which was originally designed for actions like "force click" to look up definitions [5][6]. - The application reads pressure data from the trackpad and converts it into weight readings, leveraging a private API discovered by Shah that allows real-time pressure data access [9][10]. - The app is built using SwiftUI for the interface and the Combine framework for data transmission, making it appear as a native macOS application [11]. Group 2: Technical Specifications - TrackWeight requires macOS 13.0 or higher and is compatible only with MacBook models equipped with Force Touch trackpads, specifically those released from 2015 onwards [20]. - Users must disable App Sandbox to allow the application to access low-level hardware features necessary for accurate pressure readings [20]. - The application has been open-sourced on GitHub under the MIT license, allowing for modification and distribution [13]. Group 3: User Experience and Limitations - Users must keep their fingers in contact with the trackpad while weighing objects to ensure accurate pressure data is captured [16][17]. - The application is experimental and not recommended for commercial use or scenarios requiring high precision [16]. - There are limitations, such as potential misidentification of metal objects as fingers, which can be mitigated by placing a tissue on the trackpad [19]. Group 4: Community Engagement and Future Potential - The release of TrackWeight has sparked discussions on platforms like Hacker News and Reddit, with users exploring creative applications of the technology [22]. - Some users have expressed interest in integrating similar functionalities into kitchen apps or smart home systems, indicating a potential market for such innovations [28][29].

转自：吐槽星君 五年没回家村里到处说我亖了...？ （vi a .@蒸汽波波 ） 当我吃海底捞说热时… 公众号·吐槽星君 T II 日 � r and post 4 真把朋友当立本人整啊 （vi a .@好困） 纹了人中窝还有救吗 因为朋友介绍我去纹了人中窝,图片是第一天和 第六天,现在颜色还是很深还有没有救鸽后面颜 色会变淡吗#人中窝 #纹绣 9 公众号 · 吐槽星君 C 么西 昨天 03:01 广东 回复 7.8万 0 于 , ■ . J 笑出猪叫 昨天 03:21 四川 回复 7352 展开 4061 条回复 O 事已至此,再植点毛补救一下。 1.5 万 昨天 04:42 广东 回复 学校的违纪行为有多离谱 （vi a .@萤火漫） （vi a .@ 一晒就黑 ） 改发现把同学名改成了群昵称。 1.2 万 06-20 上海 回复 展开 250 条回复 y 老师:怎么这孩子有两个妈妈开家长会时我 2410 高低得看看 3 06-22 新疆 回复 展开 42 条回复 O 班主任在群里发游戏助力 1152 9 公众号 · 吐槽星君 疫情的时候做了一个桔子口罩被抓了 20 回复 2天前·四川 3.9万 众号 · ...

梦晨 发自 凹非寺 量子位 | 公众号 QbitAI OpenAI掌门人奥特曼，可能是GPT-5发布前的最后一次深度访谈。 虽然我很快就投入到下一件事中，但那种感觉没有消散。我在自己应该擅长的领域感到了无用感，而AI轻而易举就解决了。" 这一次，奥特曼透露了上手GPT-5后的 "天啊时刻" ：我往后靠在椅子上，感到一阵眩晕， 在自己擅长的领域感到了无力 。 最近一段时间，不论奥特曼、OpenAI官方账号还是OpenAI员工都在反复提醒大家： GPT-5 很快就要 发布 。 在发布前，与主持人 Theo Von 长达一个半小时的对话中，奥特曼抛出了一连串惊人观点： 他的孩子将永远不会比AI聪明，这从出生那一刻就注定了 AI CEO可能不会太久就接管OpenAI，"到时候我会找别的事做" 现有的硬件配不上人工智能的能力 …… 测试GPT-5的"天啊"时刻 故事要从一封邮件说起。当天早上，奥特曼收到一个自己连问题都搞不懂的邮件，他抱着试试看的心态输入到GPT-5中，结果瞬间得到了完美 答案。 奥特曼回忆道： 我真的坐在那里愣了一会儿，这是那种"天啊，来了"的时刻。 这种体验让他意识到，很多人担心的那种被AI超越的感 ...

Core Viewpoint - The article emphasizes the importance of integrating existing programming skills with large model technologies to enhance career prospects in the AI field, rather than abandoning current skills [1]. Summary by Sections Course Overview - A course titled "Large Model Application Development Practical Training" is designed to help developers master AI application development from scratch through practical projects and code breakdowns [1]. - The course includes insights from industry experts and real case studies from major companies, providing participants with high-paying job opportunities and internal referrals [1][15]. Course Content - The curriculum covers essential concepts such as RAG (Retrieval-Augmented Generation), AI Agent, and Transformer architecture, focusing on practical applications and fine-tuning techniques [9][11]. - It consists of five modules: basics, tools, advanced topics, competitions, and practical applications, ensuring a comprehensive learning path [9]. Target Audience - The course is aimed at developers looking to connect with product teams, build technical barriers, avoid job insecurity, and enhance their skills for future career development [13]. - It is particularly relevant for programmers concerned about job stability as they age, especially those nearing the 35-year mark [13]. Success Metrics - The course has successfully served over 20,000 students, receiving positive feedback and helping many secure high-paying job offers [11]. - Participants learn to customize models for specific industries such as manufacturing, healthcare, and finance, improving task accuracy and efficiency [11]. Practical Experience - The course includes detailed case studies of popular AI applications, allowing participants to gain hands-on experience and build a portfolio of practical projects [16]. - Students will learn to implement AI technologies in various business scenarios, enhancing their employability [16]. Career Development - The course offers insights into current job market trends for large model technologies, including salary expectations and career growth opportunities [20]. - Continuous internal referral opportunities are provided, ensuring participants have a direct pathway to high-paying positions in leading companies [20].