Core Viewpoint - The article emphasizes the urgent need for AI-related skills in the job market, highlighting a significant demand for professionals who can work with AI technologies, particularly in large companies, where salaries can reach 700,000 to 1,000,000 CNY annually for those with relevant skills [1][3]. Group 1: AI Talent Demand - The demand for AI-skilled professionals is far greater than the supply, creating a substantial opportunity for those looking to advance their careers or transition into AI-related roles [3][4]. - Companies are particularly interested in candidates who understand AI application development technologies such as RAG, Agent, fine-tuning, and Function Call, which are essential for creating popular applications like intelligent customer service and AI assistants [1][15]. Group 2: Training and Development Opportunities - A practical course titled "Large Model Application Development Practical Training Camp" is being offered to help individuals quickly acquire foundational knowledge in AI model principles, application technologies, and project experience [3][7]. - The course is designed for all technical professionals, regardless of their current role, and aims to facilitate career transitions into high-paying AI positions [4][11]. Group 3: Course Features and Benefits - The course includes insights from industry experts, covering the principles of large models, practical applications, and career development strategies, along with continuous job referral opportunities [9][12]. - Participants will gain hands-on experience through case studies and project simulations, which can be directly added to their resumes, enhancing their employability [12][18]. - The training program has successfully served over 20,000 students, with many achieving high-paying job offers after completion [17].

Group 1 - The core viewpoint of the article revolves around the controversial sale of the open-source project Alist, which has raised significant concerns within the community regarding transparency and trust [1][2][3] - The original developer Xhofe's response to the community's concerns was seen as vague and insufficient, failing to deny the sale and not providing details about the transaction or the new owner's identity [2][3] - The new owner, Guizhou BuG Technology, has a history of controversial practices in the open-source community, leading to fears of "open-source hijacking" through their typical strategy of acquisition, document modification, and monetization [4][6] Group 2 - The community is taking proactive measures in response to the situation, including calls to freeze updates to the Alist project to avoid potential supply chain poisoning risks [7] - A fork of the project has been initiated by a core contributor, indicating a movement towards alternative solutions and a rejection of the new ownership [7] - Users are advised to take precautions such as unbinding sensitive accounts and using independent API keys to mitigate risks associated with centralized services [9]

Core Viewpoint - Google has officially released Android 16, introducing significant updates in notification systems, hearing aid compatibility, security features, and productivity enhancements for tablets, marking one of the earliest major version updates in recent years. Group 1: Notification System - Android 16 introduces real-time dynamic updates in the notification system, allowing users to receive live information from compatible apps without frequently opening them [1] - The system automatically groups notifications from the same app, effectively reducing information overload and creating a more organized notification interface [2] Group 2: Hearing Aid Compatibility - The update significantly enhances the experience for users of hearing aids, allowing them to switch to the phone's microphone for clearer voice quality even in noisy environments [3] - Additionally, Android 16 includes native controls for hearing aids, enabling users to conveniently adjust volume and settings directly from their phones [6] Group 3: Security Features - Android 16 introduces an "Advanced Protection" feature, which is Google's strongest mobile device protection solution to date [7] - This feature includes a range of robust security measures to effectively combat network attacks, malicious apps, unsafe websites, and scam calls, providing comprehensive security for users [8] Group 4: Productivity Enhancements for Tablets - The update collaborates with Samsung to develop a desktop window mode for tablets, allowing users to open, move, and resize multiple app windows simultaneously, significantly improving cross-application work efficiency [9] - This feature will be available on compatible devices later this year, with future updates expected to bring customizable keyboard shortcuts, taskbar overflow functionality, and external display extensions [10] Group 5: Additional Features - Android 16 also includes practical features such as HDR screenshots, adaptive refresh rates, and authentication options [11] - More updates to the Material 3 Expressive design are anticipated later this year, further enhancing the system's visual experience and usability [11]

Core Viewpoint - The introduction of Apple's "Liquid Glass" design language at WWDC 2025 is being compared to Microsoft's Windows Vista Aero Glass design, sparking discussions about innovation versus nostalgia in UI design [3][20]. Group 1: Design Comparison - Apple's "Liquid Glass" is described as the largest visual innovation since iOS 7 in 2013, aiming for a unified and immersive experience across all operating systems [3][19]. - Many users have criticized the "Liquid Glass" design as unattractive, with comparisons drawn to Windows Vista's design, which featured semi-transparent windows and soft gradient effects [5][11]. - The similarities between "Liquid Glass" and Vista Aero Glass are evident in their use of transparency and light reflection, leading to a resurgence of nostalgia among users [7][12][18]. Group 2: User Reactions - Social media platforms have seen a surge of reactions, with users posting side-by-side comparisons of "Liquid Glass" and Vista designs, leading to trending topics [12][15]. - Some users humorously suggested that Apple has "accidentally traveled back to 2006" due to the design's resemblance to older Windows aesthetics [12][15]. - The feedback includes both criticism of Apple's lack of innovation and a sense of nostalgia for the Vista era [15][20]. Group 3: Developer Challenges - Developers will face significant challenges in adapting to the new "Liquid Glass" design language, as Apple plans to release updated APIs for various devices [19]. - This adaptation is considered the most substantial UI design adjustment since the release of iOS 7, requiring developers to ensure functionality aligns with the new visual effects [19][20]. Group 4: Industry Impact - The "Liquid Glass" design reflects a continuation of the industry's trend towards transparent design, building on previous iterations by Apple and Microsoft [16][18]. - The reception of this design will ultimately determine whether it is viewed as a bold innovation or a retro homage to past design styles [20].

Core Viewpoint - The article emphasizes that AI large models are not only replacing traditional CRUD development models but also reshaping the career landscape for programmers, leading to both technical anxiety and survival crises for those in the industry [1] Group 1: Industry Trends - Major industries such as manufacturing, healthcare, and finance are accelerating the application of AI, with companies increasingly valuing talent that can leverage AI large model technology to reconstruct business processes [1] - Intel's recent announcement of laying off 20,000 employees highlights the shrinking of traditional roles, while AI-related positions are experiencing significant growth, offering salaries of up to 1 million annually for those with 3-5 years of experience [1] Group 2: Learning Opportunities - The article promotes a free course titled "Large Model Application Development Practical Training Camp," aimed at equipping technical professionals with knowledge of AI large model principles, application technologies, and practical project experience [1][4] - The course includes live sessions covering the career prospects of large model applications, typical business scenarios, and technical architectures, as well as hands-on training in fine-tuning AI models [2][6] Group 3: Practical Skills Development - The training program is designed to help participants understand the core principles and applications of large models, including the use of RAG and fine-tuning techniques to enhance language model performance [6][15] - Participants will gain practical experience by working on popular AI projects, which can be directly included in their resumes to improve job prospects [15][20] Group 4: Career Advancement - The course offers insights from industry leaders and provides opportunities for internal referrals to major companies, helping participants navigate the job market and secure high-paying positions [20][21] - The urgency of the course is emphasized, with limited spots available and a call to action for individuals to take proactive steps in mastering AI large model technologies to avoid being left behind in the evolving job landscape [1][13]

Mumbai：印度孟买， 常被视为提供廉价技术劳动力的地区 真 AI、真 LLM、真 API… ↓↓↓ Gujarati：印度的古吉拉特邦，以商业著称 往期趣图 （点击下方图片可跳转阅读） ...

Core Insights - The article discusses the transformative updates presented at WWDC 2025, focusing on software architecture, design language, and AI infrastructure, despite the lack of hardware surprises [1][2]. Group 1: Liquid Glass Design Language - Apple introduced the "Liquid Glass" design language, marking the most significant visual innovation since the flat design in 2013. This semi-transparent material reflects and refracts the surrounding environment, dynamically responding to user actions [3]. - Developers are advised to prioritize using system-provided UIBarAppearance for navigation bars and implement UIBlurEffect for a layered glass effect. Xcode 17 includes design review tools to automatically detect visual inconsistencies [4]. Group 2: Foundation Models Framework - Apple has opened its device-side foundational model framework to developers, which is crucial for building AI functionalities. This includes a unified design standard across all platforms (iOS, iPadOS, macOS, watchOS, tvOS, and visionOS), significantly reducing multi-platform adaptation costs [5]. - New UIVisualEffectView subclasses support glass-like effects, and developers must ensure correct layering of semi-transparent effects in existing applications [5]. - The CoreML's FMFramework allows developers to directly call a 30 billion parameter model on-device for tasks like text generation and image understanding, adhering to Apple's privacy standards [6]. Group 3: iPadOS 26 Productivity Revolution - iPadOS 26 introduces true background multitasking, allowing developers to utilize the new UIWindowScene API for flexible window management. Existing applications using private APIs for window management should transition to official multi-window APIs [9][11]. - The new API supports free scaling and layered window management, while the BGProcessingTask enables computation-intensive background tasks, suitable for video rendering and document processing [11]. Group 4: Xcode 17 and Swift 6 Updates - The development toolchain has received significant upgrades, including the integration of Swift Assist, an AI-based code completion tool that improves accuracy by 40% compared to its testing version [13]. - Swift 6 introduces features such as complete data race safety, enhanced macro systems, and improved testing tools with visual test orchestration [13]. Group 5: visionOS 26 Spatial Computing Expansion - The Vision Pro ecosystem continues to evolve with new features, including support for third-party controllers and the GazeInteraction framework, enabling innovative interactions like gaze scrolling and focus magnification [14].

Core Viewpoint - The article discusses the cost-effectiveness of deploying AI models like DeepSeek-V3 at scale compared to running them locally, highlighting the trade-off between throughput and latency in AI inference services [2][13]. Group 1: Cost and Performance of AI Models - DeepSeek-V3 appears to be fast and cost-effective for large-scale deployment, but running it locally is slow and expensive due to low GPU utilization [2][13]. - The fundamental trade-off in AI inference services is between high throughput with high latency and low throughput with low latency [2][11]. Group 2: Batch Inference - Batch inference allows for efficient processing of multiple tokens simultaneously, leveraging GPU capabilities for large matrix multiplications (GEMM) [3][11]. - The implementation of inference servers involves receiving requests, pre-filling prompts, queuing tokens, and processing them in batches to maximize GPU efficiency [4][11]. Group 3: GPU Efficiency and Model Design - High batch sizes are necessary for models like expert mixture models (MoE) to maintain GPU efficiency, as they require many small multiplications unless batch processing is employed [7][11]. - Large pipelines in models necessitate high batch sizes to avoid pipeline bubbles, ensuring that GPUs remain active throughout the inference process [8][9]. Group 4: Latency and Throughput Trade-offs - Increasing batch size can lead to higher latency as users may need to wait for enough tokens to fill a batch, but it significantly improves throughput [11][12]. - The choice of batch size and collection window directly impacts the balance between throughput and latency, with larger windows helping to avoid pipeline bubbles [9][11]. Group 5: Implications for AI Service Providers - AI service providers must select batch sizes that eliminate pipeline bubbles and keep experts saturated, which often results in higher latency for improved throughput [11][13]. - The architecture of models like DeepSeek may not be easily adaptable for personal use due to their low efficiency when run by a single user [13].

算法是程序员的内功！「算法爱好者」专注分享算法相关文章、工具资源和算法题，帮程序员修炼内 功。 5 月 14 日，微软在 全球范围内大裁员，优化比例 3% 的六七千人，波及全球多个部门与业务线，包括 LinkedIn、Xbox、Azure、工程研发等。 以下文章来源于算法爱好者 ，作者小蒜 算法爱好者 . 详情可看之前的相关推文： 3 名微软员工因裁员离世 4 天前，有人在国外职场社交平台 Blind 发帖称，有 3 人因被微软裁员而自杀了。 PS：Blind 平台需用公司邮箱注册验证身份，确保参与者为真实职场人士，但发帖/评论时完 全匿名，保护隐私。 有人爆料称，他们认识全球范围内的 3 个人，这些人被裁员后极度抑郁，最终选择了自杀。其中一人曾被其经 理严重苛待。 我们经常谈论心理健康，但很少谈及有毒的裁员文化是如何催生或加剧心理问题的。那种持续的恐惧，裁员的 方式，以及之后的沉默。如今，这正在危及生命。 微软或其他任何公司何时才会为其造成的情感伤害承担责任？还要有多少人丧生，我们才会承认这并不正常？ 如果你正在苦苦挣扎，请记住：你的工作并非你的价值所在。你并不孤单，而且有办法获得帮助。总会有另一 条路可走 ...

参考：周鸿祎微博 + 证券时报 2024 年年初，周鸿祎频繁谈及网红经济，并表示自己想做网红。谈及原因，周鸿祎表示，马斯克、余承东、 雷军等都是网红企业家，通过他们不断的各种演讲、各种传播，周鸿祎认为他们每个人至少帮助自己所在的企 业节省了数十亿元广告费。 周鸿祎表示，"我也希望，通过我和粉丝的互动，通过我的短视频，通过我的直播，能够让中国数以百万计、 千万计的用户能够了解我们的战略，了解我们的技术，了解我们的产品。我也希望未来我能够替 360 节省上 10 亿元的广告费。" 近日，360 集团创始人、董事长兼 CEO 周鸿祎发视频称，"我准备干掉 360 整个市场部，这样一年可以给公 司省下几千万元。" "听起来像天方夜谭，但这次我准备动真格的了。" 周鸿祎表示，"从今天起我要准备做一个挑战，我一个人要 完成一场完整的新产品发布会。" "这件事我如果干成了，就意味着 AI 智能体确实有颠覆性的发展，传统的效率模型可能要被淘汰了，360 市场 部也可以全部转岗到其它部门或者都给我编智能体去。" - EOF - 推荐阅读 点击标题可跳转 1、 马斯克再次开启 7x24 工作模式.网友：比 996 还疯狂的节奏 ...