Core Viewpoint - The article discusses the perception of job-hopping among high-value talent versus ordinary workers, highlighting that the former is often viewed positively while the latter may face negative judgments regarding stability and capability [5][6][7]. Group 1 - High-value talent, such as former OpenAI engineer Yao Shunyu, is seen as making career moves that reflect ambition and a desire for growth, rather than instability [4][5]. - Ordinary workers, on the other hand, may be labeled as lacking stability or capability when they change jobs frequently, which can lead to negative consequences during resume screenings by employers [6][8]. - The article suggests that the rules governing perceptions of job-hopping are often biased against ordinary workers, while high achievers are not bound by the same standards [7][8].

Core Viewpoint - The article discusses a significant surge in memory prices, driven primarily by the increasing demand from AI applications, leading to a global memory shortage that affects various sectors, including PCs and gaming [2][3][30]. Group 1: Memory Price Surge - Memory prices have skyrocketed, with a 64GB memory stick that cost $350 two months ago now priced at $2,500 [4][12]. - The price of DDR5 contract memory has increased by 123% from the beginning of the year [21]. - The price of 12GB LPDDR5X memory chips for Apple's iPhone 17 series has risen to approximately $70, compared to $25-$29 a year ago, indicating a 2-3 times increase [14][15]. Group 2: AI's Impact on Memory Demand - AI servers require significantly more memory, with DRAM needs being about eight times that of standard servers [34]. - Major companies like OpenAI are securing large quantities of DRAM, locking in 40% of monthly production capacity from suppliers like Samsung and SK Hynix [36][38]. - The shift in demand towards AI products has led memory manufacturers to prioritize high-margin products, resulting in reduced availability of traditional memory for consumer electronics [46][48]. Group 3: Supply Chain and Market Dynamics - Major PC manufacturers, including Lenovo and HP, are preemptively signing procurement agreements with memory suppliers to secure future supplies [20]. - The transition of production lines from traditional DDR4 to high-bandwidth memory (HBM) and DDR5 is causing a significant reduction in the availability of mid-range memory [49][53]. - The memory shortage is expected to persist until at least 2026, with AI consuming 20% of global DRAM wafer capacity [53]. Group 4: Broader Market Implications - The memory crisis is reshaping the smartphone and PC markets, with manufacturers facing tough choices between raising prices or reducing specifications [82][84]. - The cost of memory components is becoming a critical factor in the pricing structure of smartphones, where memory can account for 10%-20% of the bill of materials [82]. - The article suggests that 2026 may see a significant increase in technology product prices due to the ongoing memory shortage driven by AI data centers [86].

目前网上骂声挺多的，不知道某宝后续会如何回应？ 有位自称"程序员"的网友是这样解释的，大家认同么？ 晚上刚刷到的一条热搜： 骑手实测平台1分钟现实才42秒 更完整的计时对比视频如下： ...

Core Insights - The article discusses the transformative impact of AI on programming practices, highlighting a shift from traditional coding to AI-assisted development, particularly through tools like Claude Code [3][6][10]. Group 1: Changes in Work Practices - In 2025, the author experienced significant changes in their work style, moving from manual coding to relying heavily on AI tools for programming tasks [6][10]. - The author published 36 articles in a year, reflecting a newfound engagement with AI topics and a shift in focus towards AI-driven programming [7][9]. Group 2: AI Tools and Their Impact - The emergence of tools like Claude Code has revolutionized coding practices, allowing developers to automate routine tasks and focus on higher-level responsibilities [9][10]. - The integration of large language models (LLMs) with tool execution capabilities has proven to be highly effective, enhancing productivity and enabling new functionalities [10][12]. Group 3: Human-Machine Relationship - The article explores the evolving relationship between developers and AI, noting a tendency to anthropomorphize AI tools, which raises questions about their role and the emotional responses they elicit [12][13]. - There is a growing concern about the implications of assigning human-like qualities to machines, emphasizing the need for clarity in defining the relationship between humans and AI [12][13]. Group 4: Future Directions - The author identifies several areas for future development, including the need for new version control systems that can accommodate AI-generated code and improve collaboration [22][24]. - There is a call for innovative code review processes that align with AI workflows, as current systems are not compatible with the new programming paradigms introduced by AI [24][25]. - The potential for advancements in observability tools is highlighted, suggesting that LLMs could enhance the development of more user-friendly solutions in this area [25][26].

这肯定不合理呀。 ？？？ 1、 这些小工具是 "我"在私人时间开发的，即便是基于开源项目，那它们的所有权归属于我，和"公司"没关 系。（毕竟 "我" 又不是公司员工，也没拿公司一分钱报酬 ） 2、这些小工具是 "我" 为了帮"老婆"减轻负担才开发的，是小两口之间的支持，并不是公司的工作产出，老板 的要求属于强人所难。 想留下也行，价格给到位再说。不过看发帖人的描述，"老板"大概是想白嫖了。还是尽在拜拜得了 ...

Core Insights - The article highlights the challenges faced by mid-level tech professionals in the current job market, particularly after layoffs, as exemplified by Clair Todd's experience after being laid off from Oracle [1][24]. Group 1: Career Background - Clair Todd was a core technical staff member at Oracle, working as a Site Reliability Engineer (SRE) since January 2020, enjoying a stable salary and remote work benefits [3][4]. - Prior to Oracle, she worked at Hitachi Vantara as a Quality Assurance Engineer, where she faced long commutes that affected her well-being [3][4]. Group 2: Layoff Experience - In late 2023, Clair Todd's entire team was laid off amid rumors of company-wide layoffs, which she initially hoped to avoid [5][7]. - Oracle provided severance pay, unemployment benefits, and her emergency fund, allowing her to take a break before job hunting [8]. Group 3: Job Search Challenges - Clair Todd began her job search in February 2024, optimistic due to her previous experiences, but soon faced difficulties as her applications received little response [9][10]. - The job market was polarized, with high-level positions requiring extensive experience and entry-level roles offering low salaries, leaving mid-level engineers like her in a challenging position [10][12]. Group 4: Financial Struggles - Over two years, Clair Todd depleted over $50,000 in savings due to unemployment, with her monthly expenses exceeding her income from unemployment benefits [13][14][15]. - She faced significant financial pressure, including a mortgage and $45,000 in student loans, which strained her finances further [16][17]. Group 5: Reflection and Strategy Shift - Clair Todd reflected on her career transition and questioned whether her decision to move into tech was worth the current struggles [19][23]. - After facing repeated rejections, she adjusted her job search strategy, focusing on small and mid-sized companies, which she found to have more personable hiring processes [23][24].

往期趣图 （点击下方图片可跳转阅读） 罗永浩和豆包"辩论吵架" ↓↓↓ ...

Core Insights - DeepSeek introduced a new architecture called "Manifold-Constrained Hyper-Connections" (mHC), which enhances performance with only a 6.7% increase in training time on a 27 billion parameter model [3][36]. - The mHC architecture optimizes the residual connection space by projecting matrices onto constrained manifolds, ensuring stability and significantly expanding the residual stream width without substantial computational costs [8][25]. Group 1: Performance Improvements - In system-level benchmark tests, the mHC architecture consistently outperformed baseline models and Hyper-Connections (HC) across various tasks, demonstrating its effectiveness in large-scale pre-training [22][51]. - Specific performance metrics showed that mHC achieved a 2.1% improvement on the BBH benchmark and a 2.3% improvement on the DROP benchmark compared to HC [52][54]. Group 2: Technical Details - The core idea of mHC is to restore identity mapping properties under the topology of Hyper-Connections, allowing for practical value in large-scale training and real-world foundational model tasks [25]. - mHC employs a double stochastic matrix constraint to maintain stability while enhancing the interaction between residual streams, which is crucial for maximizing the potential of multi-stream architectures [26][27]. Group 3: Engineering Optimizations - The implementation of mHC involved several engineering optimizations, including reordering operations to improve efficiency and using mixed precision strategies to maximize numerical accuracy without sacrificing computational speed [38][42]. - The DualPipe scheduling strategy was enhanced to effectively overlap communication and computation, addressing significant communication delays introduced by the n-stream residual structure [46][48].

Group 1 - The article expresses well-wishes for the new year, emphasizing the importance of overcoming challenges and celebrating achievements in coding and life [1][2][4] - It highlights the significance of maintaining connections with family and friends, suggesting that they are the most valuable dependencies in life [5] - The message encourages a positive outlook for 2026, with aspirations for success in both personal and professional endeavors, using coding metaphors to illustrate resilience and creativity [6]

趣图: 程序员合法摸鱼的最佳理由出 新了 文科生不必焦虑，AI 先干掉的是计算机专业的学生！ ↓↓↓ 往期趣图 （点击下方图片可跳转阅读） ...