Core Viewpoint - The research introduces a machine-learning-assisted strategy called CAGE-Prox vivo for precise protein activation in living organisms, providing a universal platform for time-resolved biological studies and on-demand therapeutic interventions [1][13]. Group 1: Research Background - The study emphasizes the importance of gain-of-function research in understanding biological processes and disease pathology, highlighting various protein engineering techniques that have been developed to manipulate proteins [4]. - Current techniques, while effective, often rely on complex protein constructs that may alter the natural function of target proteins [4][5]. Group 2: CAGE-Prox Strategy - CAGE-Prox is a more universal strategy for controlled activation of a wide range of protein targets, independent of the amino acid residue type at the active site [5]. - The strategy utilizes a light-degradable tyrosine residue (ONBY) to temporarily mask protein activity, allowing for high temporal resolution in studying stimulated cellular processes [5][6]. Group 3: CAGE-Prox vivo Development - The CAGE-Prox vivo strategy incorporates a non-natural amino acid, trans-cyclooctene-tyrosine (TCOY), which can be introduced near the active site of target proteins to temporarily deactivate their function [7][9]. - The research team developed an integrated machine learning process to evolve an aminoacyl-tRNA synthetase (aaRS) that can efficiently incorporate TCOY into proteins [10][11]. Group 4: Applications of CAGE-Prox vivo - The CAGE-Prox vivo system enables precise killing of tumor cells by temporarily inactivating the anthrax lethal factor (LF) and then restoring its activity through a small molecule-triggered bioorthogonal reaction [9][10]. - The strategy also allows for the construction of safer bispecific antibodies that only regain their tumor-targeting function upon specific chemical activation, reducing the risk of cytokine storms and related toxicities [11][12].

Overview of Self-Learning Edge Computing Controllers - Self-learning edge computing controllers are distributed network systems based on edge computing architecture and machine learning technology, primarily used in hotel scenarios for real-time perception, dynamic decision-making, and autonomous optimization [1][3] - Key functionalities include real-time perception, autonomous decision-making, service collaboration, and security management [3] Hotel Digitalization Industry Chain Structure - The hotel digitalization industry chain consists of digital infrastructure, digital solution providers, and digital transformation entities [1][2] - The upstream includes hardware (servers, storage devices, network devices) and software (operating systems, middleware, databases) [2] Global Market Analysis of Self-Learning Edge Computing Controllers - Global hotel revenue is projected to exceed $700 billion by 2024, with revenues of $550.15 billion in 2022 and $670.08 billion in 2023 [6] - Global hotel technology investment is expected to reach approximately $13.88 billion in 2024, with a stable investment ratio of about 1.9% [8] - The market size for global self-learning edge computing controllers is projected to be over $2.87 billion in 2024, with growth from $2.04 billion in 2022 [15] - The market concentration is moderate, with the top three companies holding a combined market share of 31.6% in 2024 [18] China Market Analysis of Self-Learning Edge Computing Controllers - China's hotel revenue is expected to exceed 370 billion yuan by 2024, with estimated revenues of 353.95 billion yuan in 2023 [19][21] - The technology investment in China's hotel industry is projected to surpass 15 billion yuan, with ratios of 4% in 2022 and 4.2% in 2023 [22] - The market size for self-learning edge computing controllers in China is expected to exceed 1 billion yuan in 2024, growing from 610 million yuan in 2022 [29] - The market concentration is high, with the top five companies holding a combined market share of 68.1% in 2024 [32]

Investment Rating - The report assigns an "Accumulate" rating for the company, marking its first coverage [1]. Core Viewpoints - The company, Zhenghai Magnetic Materials, reported a revenue of 5.539 billion yuan in 2024, a year-on-year decrease of 5.70%, and a net profit attributable to shareholders of 92 million yuan, down 79.37% year-on-year [4][13]. - In Q1 2025, the company achieved a revenue of 1.459 billion yuan, representing a year-on-year increase of 24.38%, while the net profit attributable to shareholders was 69 million yuan, showing a decline of 10.94% [14]. - The company is focusing on its core business of magnetic materials, particularly in the high-performance neodymium-iron-boron permanent magnet sector, which is facing intense competition and price pressures [5][16]. Company Overview - The latest closing price of the company's stock is 12.59 yuan, with a total market capitalization of 10.5 billion yuan [3]. - The company has a total share capital of 838 million shares, with a debt-to-asset ratio of 54.5% and a price-to-earnings ratio of 114.45 [3]. Financial Performance - The company's revenue from neodymium-iron-boron permanent magnets in 2024 was 5.494 billion yuan, down 4.79% year-on-year, with a gross profit of 779 million yuan, a decrease of 24.60% [17]. - The gross margin for 2024 was 14.18%, down 3.73 percentage points from 2023 [17]. - The company expects revenues to grow to 6.382 billion yuan in 2025, with a projected net profit of 327 million yuan, reflecting a significant recovery [8][10]. Production and Market Development - The company has a production capacity of 30,000 tons for high-performance neodymium-iron-boron permanent magnets, with a utilization rate of 84% at its Yantai base and 62% at its Nantong base [6][18]. - The shipment volume for energy-saving and new energy vehicles increased by 25% in 2024, with a total of 5.61 million sets of electric motors equipped [19]. - The company is advancing the development of non-rare earth products, which have seen a 50% increase in production, enhancing its competitive edge in the market [7][19].

Core Insights - The article emphasizes the rapid transformation of the world through artificial intelligence and programming technologies, highlighting the significance of Auckland University's computer science undergraduate program as a platform for students passionate about these fields [1]. Group 1: Program Advantages - Auckland University's computer science program boasts exceptional academic resources and a strong faculty, with the department recognized internationally for its research in artificial intelligence, data science, and cybersecurity [3]. - The faculty comprises professors from around the globe who have made significant academic contributions and maintain close collaborations with major tech companies like Google and Microsoft, integrating the latest industry trends into the curriculum [3]. - The university provides advanced learning resources, including high-performance computing clusters and virtual reality equipment, facilitating complex programming experiments and AI project development [3]. - Partnerships with numerous tech companies offer students internship and employment opportunities, allowing them to engage with real-world business projects during their studies [3]. Group 2: Application Requirements - Applicants to the computer science undergraduate program must meet specific academic and language criteria, with international students typically required to achieve an average high school score of over 80%, particularly excelling in mathematics and physics [4]. - For Chinese students, the Gaokao score is a critical reference, generally requiring a score above the provincial first-tier line; alternative qualifications like A-Level or IB scores are also accepted [4]. - Language proficiency is essential, with a minimum IELTS score of 6.5 (no individual score below 6.0) or a TOEFL score of 90 (with writing no less than 21) required for admission [4]. Group 3: Curriculum Content - The curriculum is diverse and designed to build a solid theoretical foundation and practical innovation skills, starting with introductory courses in computer science, programming basics (Python and Java), and discrete mathematics in the first year [6]. - As students progress, they encounter more specialized courses such as data structures and algorithms, computer systems principles, and database systems, deepening their understanding of computer science fundamentals [6]. - Elective courses in artificial intelligence, machine learning, computer graphics, and cybersecurity allow students to explore cutting-edge areas of interest, while project-based courses enable teamwork and problem-solving through real programming projects [6].

Investment Rating - The report assigns an "Accumulate" rating for the company, marking its first coverage [1]. Core Views - The company focuses on its core business of magnetic materials, with continuous improvements in the performance of non-rare earth products [4][7]. - The company reported a decline in revenue and net profit for 2024, with revenue of 5.539 billion yuan, down 5.70% year-on-year, and a net profit of 0.92 billion yuan, down 79.37% year-on-year [4][13]. - In Q1 2025, the company achieved revenue of 1.459 billion yuan, a year-on-year increase of 24.38%, while net profit decreased by 10.94% [14]. Company Overview - The latest closing price is 12.59 yuan, with a total market capitalization of 10.5 billion yuan [3]. - The company has a total share capital of 838 million shares, with a debt-to-asset ratio of 54.5% and a P/E ratio of 114.45 [3]. Performance Analysis - The decline in 2024 performance is attributed to intense competition in the high-performance neodymium-iron-boron permanent magnet industry, leading to price pressures and a decrease in gross margin [5][16]. - The company's neodymium-iron-boron permanent magnet revenue and gross profit for 2024 were 5.494 billion yuan and 0.779 billion yuan, respectively, down 4.79% and 24.60% year-on-year [17]. - The company has a production capacity of 30,000 tons for high-performance neodymium-iron-boron permanent materials, with a utilization rate of 84% at the Yantai base and 62% at the Nantong base [6][18]. Future Outlook - The company is expected to benefit from the continued ramp-up of the Nantong base and a rebound in rare earth prices, projecting revenues of 6.382 billion yuan, 7.141 billion yuan, and 7.872 billion yuan for 2025, 2026, and 2027, respectively [8][10]. - The projected net profits for the same years are 0.327 billion yuan, 0.393 billion yuan, and 0.491 billion yuan, reflecting significant growth [10][11].

以下文章来源于极客公园 ，作者Moonshot 极客公园 . 用极客视角，追踪你最不可错过的科技圈。欢迎同步关注极客公园视频号 一向在意公众形象的苹果，因为AI拉跨，这次被扒干净了。 文 ｜ Moonshot 编辑 ｜ 靖宇 来源｜ 极客公园（ID：geekpark） 封面来源 ｜ Unsplash 最大的巨头，在最热的潮流面前，好似隐身了。 去年6月WWDC上，苹果慢吞地发布了Apple Intelligence，可如今快一年过去，对大部分用户来说，Apple Intelligence依旧只闻其声、不见其形。 全世界都看到苹果的AI做不好了，但没人知道到底发生了什么。 知名苹果分析师Mark Gurman刚刚在外媒发出一篇长文，题为《Why Apple Still Hasn』t Cracked AI》（为何苹果仍未攻克人工智能），揭露了苹果内部对 AI态度的摇摆，内部的斗争和难以克服的技术瓶颈。 值得注意的是，Gurman用的是「Still hasn』t（仍未）」，这词就已经给苹果的现状定了调。 本文将通过重组原文以呈现苹果在AI领域的历史、现状、问题根源及未来挑战，剖析苹果为何在AI赛道上步履维艰，让AI ...

Core Insights - The article discusses the significant impact of Java programming language over the past 30 years, highlighting its evolution and continued relevance in the tech industry [1][21] - James Gosling, the creator of Java, critiques the current AI hype, labeling it as a marketing ploy and expressing skepticism about its long-term value [16][19] Java's Evolution and Impact - Java was introduced 30 years ago with the vision of "Write Once, Run Anywhere," which revolutionized software development by providing a more user-friendly alternative to C and C++ [2][3] - Despite facing competition from emerging languages, Java remains one of the most popular programming languages globally, ranking in the top ten according to Stack Overflow and fourth in the TIOBE index [3][4] - The language's enduring popularity is attributed to its reliability, backward compatibility, and focus on solving real-world problems, making it a staple in enterprise environments [20][21] James Gosling's Contributions and Views - James Gosling's journey from a curious child to a tech pioneer illustrates his innovative spirit and ability to simplify complex concepts [5][6] - Gosling emphasizes the importance of community and collaboration in the open-source movement, which he believes is essential for the continued evolution of Java [13][20] - He expresses concerns about the AI trend, arguing that it often misrepresents advanced statistical methods as autonomous systems, which could mislead investors and developers alike [16][19] Java's Technical Advancements - Recent improvements in Java include enhancements in type inference, array declarations, and significant advancements in the Java Virtual Machine (JVM) regarding memory management and garbage collection efficiency [17][18] - The JVM's ability to handle large memory spaces and its high-quality code execution have made Java particularly stable in cloud environments [10][18] Future of Programming and AI - Gosling believes that programming will remain a crucial skill, regardless of advancements in AI, and stresses the need for individuals to understand the systems they work with [19] - He critiques the notion that AI will reduce the demand for software engineers, viewing such claims as self-serving and misleading [19]

Core Insights - The company, 汇量科技, reported strong financial performance for the three months ending March 31, 2025, with a significant revenue increase and enhanced profitability [1] - The Mintegral platform's revenue reached $420.8 million, reflecting a year-on-year growth of 48.4% [1] - Net profit for the company was $19.882 million, showing a remarkable year-on-year increase of 177.9% [1] Revenue Breakdown - The intelligent bidding products, including Target ROAS, contributed over 80% of Mintegral's total revenue, highlighting their role as a key growth driver [1] - The gaming category on the Mintegral platform generated $30.57 million in revenue, marking a substantial year-on-year growth of 50.7% [2] - Non-gaming categories also performed well, with revenue of $11.51 million, representing a year-on-year increase of 42.5% [2] Strategic Developments - The company has made significant investments in AI and machine learning for its bidding systems, which have been well-received by advertisers [1] - The optimization of advertising budget structures and a more balanced business layout have been achieved through the continuous enhancement of Mintegral's intelligent bidding capabilities [2]

Core Viewpoint - The article emphasizes the importance of a seamless and secure account opening process, highlighting that while customer expectations are for a quick and easy experience, the underlying complexities involve significant costs and risks for companies [1]. Group 1: Account Opening Process - The account opening process is not just about converting potential customers but also reflects the company's values and how these values integrate with customer experience [1]. - Security is a recurring theme throughout the account opening process, affecting every aspect of the interaction [1]. - In 2023, payment fraud is estimated to have caused losses of approximately $48 billion for merchants, with expectations of continued increases by 2025 [1]. Group 2: Strategies to Prevent Fraud - Institutions can implement key strategies to prevent fraud and optimize the account opening experience, including real-time bank account verification and multi-layered authentication [2]. - Behavioral pattern analysis can help identify quality customers while excluding bad actors from the system [2]. - Strict customer due diligence (KYC) and business due diligence (KYB) processes should be combined with behavioral analysis to build a solid trust foundation throughout the customer lifecycle [2]. Group 3: Future Developments - The company is developing AI and machine learning-powered solutions to enhance the efficiency and speed of the account opening process [5]. - By integrating advanced tools into the account opening process, organizations can significantly improve data review efficiency and speed up information processing [5]. - The deployment of these solutions is expected to reduce abandonment rates during customer conversion and enhance the overall onboarding experience for both suppliers and customers [5].

Group 1 - The core idea is that coding for artificial intelligence (AI) is becoming as essential as reading and writing, with the potential to enrich lives through data utilization [1][2] - AI and data science can provide significant value across various professions, making AI-oriented coding skills more valuable than traditional coding [2][3] - The rapid rise of AI has led to an increase in job opportunities, emphasizing the importance of foundational skills, project work, and job searching in career development [3][4][6] Group 2 - Learning foundational skills in AI is a continuous process, with a focus on understanding key concepts in machine learning and deep learning [7][8] - Mathematics is crucial for AI roles, with an emphasis on linear algebra, probability, statistics, and exploratory data analysis [8][11] - Building a portfolio of projects that demonstrate skill progression is essential for career advancement in AI [24][26] Group 3 - The job search process in AI involves predictable steps, including researching roles, conducting informational interviews, and applying for positions [27][36] - Networking and building a supportive community are vital for career growth in the AI field [43][48] - The importance of continuous learning and adapting to new technologies is highlighted as a key to success in AI careers [10][41]