Core Viewpoint - The article discusses the phenomenon of "degree filtering" in major tech companies during campus recruitment, emphasizing that while educational background is considered, it is not the sole determinant for hiring decisions [2][4]. Group 1: Company-Specific Insights - Tencent is noted for considering educational background but not exclusively; there are instances of non-elite graduates being hired, albeit in low numbers [2][3]. - ByteDance has a similar approach to Tencent, where exceptional candidates from non-elite schools can still secure internships, provided they demonstrate strong skills and achievements [4][5]. - Alibaba is characterized as a "degree factory," where candidates are typically required to have a top-tier educational background, limiting opportunities for those without [4][5]. - Other companies like Baidu, Kuaishou, JD, Meituan, and Didi have seen non-elite graduates enter, especially if they have early internship experiences [5][6]. - Telecommunications companies such as Huawei and ZTE are noted for strict educational requirements, making it challenging for non-elite graduates to gain entry [5]. Group 2: Strategies for Candidates - Candidates without strong educational backgrounds are encouraged to enhance their profiles through early preparation, multiple project experiences, and internships [6][7]. - Engaging in competitive programming (e.g., ACM competitions) is highlighted as a valuable asset that can help non-elite candidates stand out [4][5]. - The article stresses the importance of not becoming complacent based on one's current academic standing, as competition is fierce against high-achieving peers [6][7].

Core Viewpoint - The article highlights the vulnerability of even long-established companies to cyberattacks, emphasizing that a single weak password can lead to catastrophic consequences, as demonstrated by the case of KNP, a 158-year-old transportation company that went bankrupt due to a ransomware attack triggered by a guessed password [2][3][7]. Group 1: Incident Overview - KNP, a historic transportation company in the UK, suffered a severe cyberattack in June 2023, leading to its collapse and the loss of over 700 jobs [3][7]. - The attack was executed by the Akira hacking group, which has targeted over 250 organizations globally since March 2023, with ransom demands exceeding $42 million [3][4]. - The method of attack involved basic techniques such as password guessing and brute force, rather than sophisticated hacking methods [4][6]. Group 2: Attack Details - After breaching KNP's internal systems, Akira deployed ransomware that encrypted all business-critical data, rendering the company unable to operate [5][6]. - The ransom demand was estimated to be around £5 million (approximately 48.49 million RMB), which KNP could not afford [5][6]. Group 3: Broader Implications - The incident is not isolated; numerous UK companies, including M&S and Co-op, have faced similar attacks, with the number of ransomware incidents in UK businesses reaching approximately 19,000 in 2024 [7][8]. - The rise of ransomware-as-a-service (RaaS) has lowered the barrier for cybercriminals, making attacks more accessible and frequent [8][9]. Group 4: Lessons and Recommendations - KNP's management has begun sharing lessons learned from the incident, advocating for a "Cyber MOT" concept, which mandates annual security assessments for companies [11][12]. - Recommendations for improving cybersecurity include implementing multi-factor authentication, prohibiting password reuse, and conducting regular employee training on cybersecurity [12].

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 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 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 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].

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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].

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