在当前贸易战带来的市场波动中，投资者如果想要寻求安全避风港，网络安全股或许是一个不错的选 择，BCA Research表示。 由于特朗普政府宣布加征关税，近几周市场剧烈震荡，标普500指数一度从2月创下的历史高点回落近 20%。但随着贸易紧张局势有缓和迹象，标普自4月8日以来反弹13%，目前年内仅下跌约5%。 尽管如此，由于缺乏实质性的进展，许多投资者仍不敢完全相信这次4月中旬的反弹。在最近的一份报 告中，BCA Research向希望对冲波动的投资者提出了一个解决方案：投资网络安全股。 "这是一个以本土市场为主的服务型行业，具有更防御性的特质，市场波动性（Beta值）低于整个科技 行业，"首席策略师Irene Tunkel写道，"它受到关税的影响较小，甚至可能从地缘政治紧张中受益，因为 客户为了防范国际网络攻击和网络犯罪而寻求保护。" Global X Cybersecurity ETF（BUG）：2025年以来上涨6%，管理费0.51%，资产规模10.5亿美元。 Amplify Cybersecurity ETF（HACK）：今年迄今上涨2%，管理费0.6%，资产接近20亿美元。 本文源自：金融界 展望未 ...

Core Viewpoint - The article discusses the limitations of copper and fiber interconnects in next-generation data centers and introduces a third solution, e-Tube, which aims to support the growing demands of AI workloads and data bandwidth requirements [1][10][16]. Group 1: Challenges in Data Center Expansion - Data center AI accelerator clusters face increasing complexity due to the emergence of new technologies, particularly generative AI and large language models (LLMs), which are pushing data bandwidth beyond traditional interconnects, rapidly doubling to 800G and soon reaching 1.6T [1]. - The need for improved performance, cost control, and energy efficiency presents significant challenges for network operators [4]. Group 2: Limitations of Current Technologies - Data centers currently rely on 400G and 800G network equipment, using copper cables for short distances and fiber optics for long distances, but both technologies are approaching their respective limits in terabit interconnect speeds [3][6]. - Copper cables, while cost-effective and reliable for short distances, suffer from channel loss due to skin effect, limiting their transmission range and scalability in high-density data centers [3][6]. Group 3: Transition to Optical Interconnects - Large-scale enterprises are shifting towards optical interconnects, such as Active Optical Cables (AOC), which can provide connections over several kilometers but come with increased complexity, power consumption, and costs, potentially up to five times that of copper cables [8]. - Optical technologies are less reliable due to performance variations with temperature changes and the eventual failure of optical components, which can also introduce significant latency [8]. Group 4: Introduction of e-Tube Technology - The e-Tube platform offers a scalable multi-terabit interconnect solution using plastic medium waveguides to transmit radio frequency data, overcoming the limitations of copper and fiber optics [10][12]. - e-Tube cables, made from low-density polyethylene (LDPE), can efficiently transmit data without the high-frequency losses associated with copper, supporting data speeds from 56G to 224G and beyond [12]. Group 5: Advantages of e-Tube - e-Tube technology results in a tenfold increase in cable coverage, fivefold reduction in weight, twofold decrease in thickness, threefold reduction in power consumption, and a thousandfold decrease in latency, all while reducing costs by three times [14]. - This technology is positioned as an ideal alternative to copper cables as data centers transition to 1.6T and 3.2T speeds, providing unique power efficiency and compatibility with existing network infrastructure [14][16].

Financial Data and Key Metrics Changes - Total revenue increased by 40% year-over-year to $1,500,000,000, while adjusted EBITDA rose by 83% to $1,000,000,000, achieving a 68% adjusted EBITDA margin [18] - Free cash flow reached $826,000,000, up 113% year-over-year, with a quarter-over-quarter growth of 19% [18][19] - The company repurchased 3,400,000 shares for a total cost of $1,200,000,000, reducing total outstanding shares to 338,000,000 [19] Business Line Data and Key Metrics Changes - The advertising business generated $1,160,000,000 in revenue and $943,000,000 in adjusted EBITDA, achieving an 81% margin [19] - Revenue growth was driven by enhancements in AI-driven technology and the full quarter impact of web-based advertising solutions [20] Market Data and Key Metrics Changes - The company reported that over 90% of its advertising revenue comes from mobile games, which are not directly impacted by tariffs [13] - The web advertising segment is still in its early stages, with less than 0.1% market penetration, indicating significant growth potential [12][14] Company Strategy and Development Direction - The company is focusing on three key priorities for 2025: improving machine learning models, advancing e-commerce and web advertising solutions, and enhancing ad testing and automated ad creation [10] - A definitive agreement has been signed to sell the games business, allowing the company to sharpen its focus on advertising [20] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's ability to grow despite macroeconomic changes, citing low market penetration and a strong demand for advertising services [14][16] - The management team emphasized the importance of continuous improvement in technology and the potential for significant growth in the web advertising space [39][40] Other Important Information - The company is set to launch a self-service dashboard for select customers, which is expected to unlock a massive opportunity for growth [12] - The adjusted EBITDA per employee in the advertising business has risen to approximately $4,000,000 annually, reflecting operational excellence [16] Q&A Session Summary Question: Guidance for next quarter and potential sequential decline in ads revenue - Management clarified that the current guidance reflects typical seasonality and that past performance is not indicative of future growth trends [29][30] Question: Category exposure and onboarding new advertisers - Management indicated that they are not actively pushing into new categories but are focused on improving self-service tools to onboard existing demand [37][39] Question: Churn among advertisers and spend per advertiser - Management reported a sub 3% churn rate for advertisers spending $250,000 annually, indicating strong retention [50][51] Question: Velocity of new web advertiser additions - Management noted that the pace of new advertiser additions has slowed due to resource constraints but expects to ramp up onboarding with the new self-service dashboard [70] Question: Self-service model expectations - Management anticipates that advertisers will gradually build budgets as they prove the effectiveness of campaigns on the new platform [83][84] Question: Contribution of non-gaming audience to total advertising revenue - Management remains optimistic about the e-commerce business potentially exceeding the previously estimated 10% contribution to total revenue [100]

Financial Data and Key Metrics Changes - Total revenue increased by 40% year-over-year to $1,500,000,000, while adjusted EBITDA rose by 83% to $1,000,000,000, achieving a 68% adjusted EBITDA margin [16] - Free cash flow reached $826,000,000, up 113% year-over-year, with a quarter-over-quarter growth of 19% [16] - The company repurchased 3,400,000 shares for a total cost of $1,200,000,000, reducing total outstanding shares to 338,000,000 [17] Business Line Data and Key Metrics Changes - The advertising business generated $1,160,000,000 in revenue and $943,000,000 in adjusted EBITDA, achieving an 81% margin [17] - Revenue growth was driven by enhancements in AI-driven technology and the full quarter impact of web-based advertising solutions [18] Market Data and Key Metrics Changes - The company is focusing on expanding into broader categories beyond gaming, with significant investments in e-commerce and web advertising solutions [5][8] - The web advertising space is still in its early stages, with less than 0.1% market penetration, indicating substantial growth potential [10] Company Strategy and Development Direction - The company is divesting its games business to sharpen its focus on advertising, with a definitive agreement signed for the sale [7][18] - Key priorities for 2025 include improving machine learning models, advancing e-commerce and web advertising solutions, and enhancing ad testing and automated ad creation [8][9] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's ability to grow through macroeconomic changes, such as tariffs, due to low market penetration [11] - The competitive landscape is viewed positively, as it drives innovation and improvement within the company [13] - The company anticipates continued strong growth, with guidance for the advertising segment projecting revenue between $1,000,000,000 and $1,215,000,000 for Q2 2025 [19] Other Important Information - The company is developing a self-service dashboard for advertisers, expected to unlock significant growth opportunities once fully rolled out [10] - The adjusted EBITDA per employee in the advertising business has risen to approximately $4,000,000 annually, reflecting operational excellence [14] Q&A Session Summary Question: Guidance for next quarter and potential sequential decline in ads revenue - Management clarified that the guidance reflects typical seasonality and emphasized that past performance is not indicative of future growth trends [22][25] Question: Category exposure and onboarding new advertisers - Management indicated that they are not actively pushing into new categories but are focused on improving self-service tools to onboard existing demand [32][34] Question: Churn among advertisers and spend per advertiser - Churn for advertisers spending $250,000 annually is under 3%, with expectations of becoming a required marketing destination for web advertisers as the product matures [44][48] Question: Velocity of new web advertiser additions - The pace of new advertiser additions has slowed due to resource constraints, but the launch of the self-service dashboard is expected to accelerate onboarding [67][70] Question: Impact of App Store regulatory news on ad spend - Management views potential fee relief for mobile games positively, as it could lead to increased ad spend from developers [126]

Core Viewpoint - By 2025, artificial intelligence (AI) has transitioned from a buzzword in tech circles to an integral part of daily life, impacting various industries through applications like image generation, coding, autonomous driving, and medical diagnosis. The evolution of AI is marked by significant breakthroughs and challenges, tracing back to the Dartmouth Conference in 1956, leading to the current technological wave driven by large models [1]. Group 1: Historical Milestones - The Dartmouth Conference in 1956 is recognized as the birth of AI, where pioneers gathered to explore machine intelligence, laying the foundation for AI as a formal discipline [2][3]. - In 1957, Frank Rosenblatt developed the Perceptron, an early artificial neural network that introduced the concept of optimizing models using training data, which became central to machine learning and deep learning [4][6]. - ELIZA, created in 1966 by Joseph Weizenbaum, was the first widely recognized chatbot, demonstrating the potential of AI in natural language processing by simulating human-like conversation [7][8]. - The rise of expert systems in the 1970s, such as Dendral and MYCIN, showcased AI's ability to perform specialized tasks in fields like chemistry and medical diagnosis, establishing its application in professional domains [9][11]. - IBM's Deep Blue defeated world chess champion Garry Kasparov in 1997, marking a significant milestone in AI's capability to outperform humans in strategic decision-making [12][14]. - The 1990s to 2000s saw a shift towards data-driven algorithms in AI, emphasizing the importance of machine learning [15]. - The emergence of deep learning in 2012, particularly through the work of Geoffrey Hinton, revolutionized AI by utilizing multi-layer neural networks and backpropagation techniques, leading to significant advancements in model training [17][18]. - The introduction of Generative Adversarial Networks (GANs) in 2014 by Ian Goodfellow transformed the field of generative models, enabling the creation of realistic synthetic data [20]. - AlphaGo's victory over Lee Sedol in 2016 highlighted AI's potential in complex games requiring intuition and strategic thinking, further pushing the boundaries of AI capabilities [22]. - The development of large language models began with the introduction of the Transformer architecture in 2017, leading to models like GPT-3, which demonstrated emergent abilities and set the stage for the current AI landscape [24][26].

Core Viewpoint - The article emphasizes the importance of constructing digital channels for businesses and individuals to stand out in a competitive environment, outlining key methods for effective digital channel development [2][4]. Group 1: Channel Planning and Positioning - Companies should develop appropriate channel strategies based on their business characteristics, market demands, and competitive landscape, clearly defining the positioning and functions of each channel [2][4]. - This includes identifying target audiences, coverage areas, and service content to ensure alignment with the company's strategic direction [2]. Group 2: Building and Optimizing Digital Channels - Establishing a diversified channel network is essential, incorporating official websites, social media platforms, and e-commerce sites to meet varied user needs [2][5]. - Enhancing user experience through improved interface design, increased interactivity, and simplified processes is crucial for boosting user satisfaction and loyalty [2]. - Strengthening brand communication via digital channels through online activities, coupons, and membership systems can attract user participation and increase channel activity and conversion rates [2]. Group 3: Data-Driven and Intelligent Operations - Utilizing big data technologies to collect and analyze user and market data is vital for understanding user needs and market changes, supporting channel optimization and decision-making [2][5]. - Implementing intelligent technologies such as artificial intelligence and machine learning can automate and enhance the efficiency and quality of digital channel operations [2]. Group 4: Channel Coordination and Integration - Effective integration of various digital channels is necessary to achieve information sharing and resource connectivity, providing consumers with a seamless shopping experience [5]. - Strengthening collaboration among different channels can enhance brand awareness and market share through online and offline interactions [5]. Group 5: Continuous Innovation and Optimization - Keeping up with technological advancements and investing in research and talent development is essential for cultivating a workforce with digital skills [5]. - Continuously optimizing channel strategies in response to market changes and user demands ensures adaptability and competitiveness in digital channel construction [5].

Core Viewpoint - The article highlights the challenges in semiconductor parameter extraction due to the complexity of device models and the inefficiencies of traditional optimization algorithms. It introduces Keysight's ML Optimizer, a machine learning-based global optimizer that significantly improves the parameter extraction process, reducing the time from days to hours and enhancing accuracy and consistency in model fitting [1]. Group 1: Challenges in Semiconductor Parameter Extraction - The complexity of semiconductor device models has made parameter extraction increasingly challenging [1]. - Traditional optimization algorithms struggle with unclear gradient changes, often getting trapped in local optima, leading to unsatisfactory extraction results [1]. - The presence of numerous interrelated parameters in modern semiconductor models further complicates the efficiency of traditional methods, requiring engineers to break down the extraction process into lengthy sub-steps [1]. Group 2: Introduction of ML Optimizer - Keysight has launched the ML Optimizer, which utilizes machine learning to provide a revolutionary solution for semiconductor parameter extraction [1]. - The ML Optimizer can process vast amounts of data and parameters in a single step, greatly simplifying the extraction workflow [1]. - The time required for parameter extraction is reduced from several days to just a few hours, significantly enhancing work efficiency [1]. Group 3: Advantages of ML Optimizer - The ML Optimizer excels in navigating non-convex parameter spaces, overcoming the limitations of traditional methods [1]. - It employs advanced machine learning algorithms to more accurately identify global optima, improving the precision of parameter extraction [1]. - The overall consistency of model fitting is enhanced, providing a solid foundation for the accurate construction of semiconductor device models [1].

Core Insights - The 42nd International Conference on Machine Learning (ICML) will be held in Vancouver, Canada, from July 13 to 19, 2025, with a significant increase in submissions this year [1] - A total of 12,107 papers were submitted, marking a 28% increase from the previous year, with an acceptance rate of 26.9% as 3,260 papers were accepted [1] - The article discusses both high-quality accepted papers and controversial rejected papers, providing a platform for discussion among researchers [1] Accepted High-Quality Papers - Spotlight papers are the highest recommended by ICML, including notable titles such as "Neural Discovery in Mathematics" and "Monte Carlo Tree Diffusion for System 2 Planning" [3][5] - The paper "MARS: Unleashing the Power of Variance Reduction for Training Large Models" achieved an average score of 4.25, showcasing a variance reduction adaptive optimizer framework with a convergence rate of (T⁻²/³), outperforming AdamW's (T⁻¹/²) [7][8] - "EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents" received an average score of 4.5 and includes 1,128 test tasks across various environments [10] Controversial Rejected Papers - Some rejected papers, despite high evaluations, have raised concerns among researchers regarding the review process [12][15] - Instances of low-quality reviews and discrepancies in scoring have been reported, with some researchers receiving incomplete and irrelevant feedback [18][20] - The article highlights the contradictions in the review process, where some papers with lower scores were accepted while higher-scoring papers were rejected [12][20]

Core Viewpoint - MHmarkets aims to enhance forex trading efficiency through innovative technologies, focusing on smart algorithms, real-time data analysis, and user experience optimization. Group 1: Technology Innovation - Smart algorithms optimize trading strategies, improving market adaptability and data analysis accuracy [4][7] - Automation systems and low-latency technology ensure efficient trade execution [5][10] - Artificial intelligence and blockchain drive technological innovation, enhancing market competitiveness [7][15] Group 2: Data Analysis and Market Prediction - Big data analysis allows for more accurate market trend predictions, reducing uncertainty in decision-making [8][9] - Real-time data analysis improves market transparency and optimizes trading decisions [8][9] Group 3: User Experience Enhancement - User interface improvements and security measures enhance overall user experience [6][12] - Simplified trading processes increase operational efficiency for users [12] Group 4: Security Measures - Advanced data encryption techniques ensure user information security during transactions [13] - Account security management focuses on password complexity and two-factor authentication [13][15] - Continuous updates to security protocols help prevent hacking attempts [15] Group 5: Customer Support and Service - Multi-channel customer communication enhances customer experience and satisfaction [17] - 24/7 technical support ensures timely resolution of customer issues [18] - Personalized customer service strengthens loyalty and satisfaction [18] Group 6: Future Directions - Focus on the potential applications of AI and blockchain in forex trading [19] - Strategies for optimizing user experience and expanding into global markets [19][20]

Core Insights - In 2025, investors face unprecedented complexities due to global economic fluctuations, Federal Reserve policy shifts, and geopolitical conflicts, leading to a revaluation of gold and the dollar [1] - Velos Markets is leveraging technology-driven investment strategy optimization tools to provide professional investors with pathways to certainty in opportunities [1] Market Trends - The gold market serves as a safe haven during economic turmoil, with price fluctuations driven by multiple factors, including Federal Reserve monetary policy signals [4] - Historical data analysis by Velos Markets indicates a 78% probability of gold price increases within three months when the U.S. core PCE price index rises over 3% year-on-year [4] - Velos Markets employs a unique three-dimensional analysis model to track central bank gold reserves, analyze CME gold futures positions, and monitor geopolitical risk indices [4] Strategy Logic - Velos Markets integrates machine intelligence with investment wisdom, offering dynamic asset allocation engines that automatically generate asset portfolios based on user risk assessments [5] - Conservative strategy includes 40% allocation to gold spot contracts, complemented by treasury futures and money market funds, while aggressive strategy allocates 25% to cryptocurrency derivatives [5] - The system dynamically adjusts strategies based on market conditions, such as increasing gold hedge positions when the VIX index rises over 15% in a day, demonstrating effective risk management [5] Tool Evaluation - Defensive tools include gold spot contracts optimized for liquidity, with cost savings comparable to a 15% discount on highway tolls during peak times [7] - Balanced tools utilize volatility-neutral combinations of gold ETFs and dollar index futures, enhancing market noise filtering efficiency to 82% during high-frequency events [8] - Aggressive tools integrate 13 technical indicators and fundamental factors to generate visual trading signals, improving the Sharpe ratio of trend strategies from 1.3 to 2.1 [9] Operational Guidelines - The first step involves account diagnosis, where users input existing holdings and risk tolerance to generate a "health score" [11] - The second step is strategy simulation, allowing users to observe performance during historical crises [12] - The third step involves selecting a main strategy framework based on diagnostic results [12] - The fourth step focuses on real-time monitoring of key warning indicators [12] - The final step emphasizes dynamic optimization and iteration of strategies based on the latest market data [12] Conclusion - Velos Markets aims to help investors establish a "probability advantage" by transforming ambiguous experiential judgments into executable signal systems [13] - The integration of technology and investment wisdom is redefining the keys to certainty in opportunities [14]