Core Viewpoint - The Zacks Transportation - Shipping industry is facing challenges such as inflation, high interest rates, tariffs, and supply chain disruptions, but there are positive factors like a 90-day extension on tariffs against China, low oil prices, and improved demand for goods and commodities post-pandemic [1][4]. Industry Overview - The Zacks Transportation - Shipping industry is cyclical and primarily provides liquefied natural gas and crude oil marine transportation services under long-term contracts with major energy and utility companies. The industry is heavily reliant on the health of the economy, with a recovery from COVID-19 standstill benefiting its prospects [3]. Shipping Industry Trends - The extension of the tariff deadline on Chinese goods is a significant positive for the shipping industry, likely leading to a short-term increase in imports and stabilizing global trade flows [4]. - Elevated compliance costs due to regulations and rising technology-related expenses are expected to impact profits in the short term, but these investments will support long-term margins [5]. - The demand for liquefied natural gas (LNG) is increasing, particularly due to geopolitical factors, which is favorable for shipping stocks [6]. - Low oil prices are beneficial for the industry as they reduce fuel costs, which are a major expense for transportation companies. Oil prices have declined by 6% in the April-June period, benefiting oil tanker companies [7]. Industry Performance - The Zacks Transportation - Shipping industry has underperformed compared to the S&P 500 index, declining by 20.2% over the past year, while the S&P 500 increased by 16% [11]. - The industry currently has a Zacks Industry Rank of 98, placing it in the top 40% of 246 Zacks industries, indicating positive near-term prospects [9]. Valuation - The industry is trading at a forward price-to-earnings (P/E) ratio of 6.82X, significantly lower than the S&P 500's 22.86X and the sector's 14.36X [14]. Stock Recommendations - Dorian LPG has seen a stock increase of 56% over the past six months, driven by rising demand for liquefied petroleum gases [16]. - Euroseas has gained 41% over the past year, benefiting from profitable contracts and a time charter equivalent rate exceeding $30,000 per day [20]. - Ardmore Shipping's stock has increased by 18% over the past six months, with a focus on product and chemical tankers [23].

As filed with the U.S. Securities and Exchange Commission on August 22, 2025. Registration No. 333- UNITED STATES SECURITIES AND EXCHANGE COMMISSION WASHINGTON, D.C. 20549 FORM S-1 Pattern Group Inc. (Exact Name of Registrant as Specified in Its Charter) (State or Other Jurisdiction of Incorporation or Organization) Delaware 5961 83-2556861 (Primary Standard Industrial Classification Code Number) 1441 West Innovation Way, Suite 500 Lehi, UT 84043 (866) 765-1355 (Address, Including Zip Code, and Telephone Nu ...

RT Avi Chawla (@_avichawla)You are in an ML interview.Your interviewer asks: "Why is Kernel Trick called a Trick?"Here's how to answer (with simple maths): ...

Industry Overview - The Zacks Computer - Networking industry is poised for growth driven by advancements in cloud computing, network security, big data, and next-gen connectivity, particularly due to the increasing applications of AI technology [1] - The demand for AI workloads and hyperscale data centers is leading to significant investments in high-speed interconnects, optical networking, and Ethernet switches, with companies aiming to leverage the multi-billion-dollar AI infrastructure opportunity [1] - The rapid deployment of 5G technology is enhancing the Internet of Things (IoT), Advanced Driver Assistance Systems, AR/VR devices, and 5G smartphones, thereby increasing the need for robust networking infrastructure [1] Trends Influencing the Industry - The Wi-Fi 7 upgrade cycle is expected to stimulate demand for innovative networking products, benefiting major players like Cisco Systems, Extreme Networks, and RADCOM [2] - The industry is experiencing heightened uncertainty due to global macroeconomic conditions and volatile supply-chain dynamics, with some telecom operators reducing or delaying capital expenditures [2][7] - The growing popularity of smart home products and IoT devices is driving innovation in networking technologies, including network virtualization and Software-Defined Networking [4] Performance Metrics - The Zacks Computer - Networking industry has outperformed the S&P 500 Composite and the broader Zacks Computer and Technology sector, gaining 31.3% over the past year compared to the sector's 18.3% and the S&P 500's 13.9% [11] - The industry is currently trading at a forward 12-month price-to-earnings (P/E) ratio of 20.27X, which is lower than the S&P 500's 22.52X and the sector's 27.18X [14] Company Highlights - **Extreme Networks**: The company reported a 20% year-over-year revenue growth in the last quarter, driven by strong demand for its AI-driven cloud networking solutions. Its SaaS annual recurring revenues rose 24.4% year-over-year to $207.6 million [18][19] - **Cisco Systems**: Cisco is enhancing its AI capabilities across its security and collaboration platforms, with notable developments including the launch of AI-driven solutions and partnerships with NVIDIA to create AI-ready data center networks [23][24] - **RADCOM**: The company focuses on cloud-native, automated service assurance for 5G networks and aims for a revenue growth target of 15%-18% for the full year, translating to a midpoint projection of $71.1 million [28][31]

Industry Overview - The electronics manufacturing services (EMS) industry provides design, engineering, and manufacturing services to electronics original equipment manufacturers (OEMs) and is currently ranked in the top 4% of the Zacks Industry Rank [1] - The industry has delivered a remarkable 102.8% return over the past year and a 48.7% year-to-date return, indicating strong performance and potential for continued outperformance in the next three to six months [2] Company Analysis: Celestica Inc. (CLS) - Celestica Inc. is a leading global EMS provider, offering a wide range of manufacturing and supply-chain solutions tailored to various customer needs [6] - The company is experiencing strong demand in the Connectivity & Cloud Solutions segment, particularly in its Hyperscaler Portfolio Solutions networking business and optical programs [7] - Celestica is well-positioned in the AI infrastructure market, projected to reach $223.45 billion by 2030, with a compound annual growth rate of 30.4% from 2024 to 2030 [8] - For 2025, the Zacks Consensus Estimate indicates revenues of $11.63 billion (up 20.6% year over year) and earnings per share of $5.55 (up 43% year over year) [11] - The short-term average price target for CLS shares suggests a potential increase of 13.3% from the last closing price of $181.34, with a maximum upside of 35.1% [13] Company Analysis: Jabil Inc. (JBL) - Jabil Inc. is a major global supplier of EMS solutions, providing design, production, product management, and after-market services across various industries [14] - The company is benefiting from strong momentum in capital equipment, AI-powered data center infrastructure, cloud, and digital commerce sectors [15] - Jabil plans to invest $500 million to enhance its manufacturing capabilities for the AI data center vertical, strengthening its position in the AI hardware supply chain [17] - For fiscal 2026, the Zacks Consensus Estimate shows revenues of $30.93 billion (up 6.1% year over year) and earnings per share of $11.05 (up 17.8% year over year) [22] - The short-term average price target for JBL shares indicates a potential increase of 14.5% from the last closing price of $204.05, with a maximum upside of 24.9% [23]

Investment Models - AI 和机器学习创建的复杂投资模型优于简单的模型 [1] - 一篇论文声称复杂的投资模型表现优于简单的模型，引发了强烈反对 [1]

Market Overview - The Digital Shipyard Market is projected to grow from USD 1.3 Billion in 2022 to USD 5.5 Billion by 2030, at a CAGR of 19.1% during the forecast period [1] - Integration of digital technologies such as digital twin, artificial intelligence, machine learning, IoT, and additive manufacturing enhances coordination and efficiency in shipbuilding [1] Digital Shipyard Concept - A Digital Shipyard integrates system- and/or cloud-based solutions to coordinate, monitor, and improve ship manufacturing, maintenance, and support processes [2] - It replaces outdated technology with unified planning tools and a common repository of design data that is always updated and accessible [2] Key Players - Siemens (Germany) offers a comprehensive portfolio covering all aspects of the ship lifecycle and aims to expand its product offerings in the digital shipyard market [3] - Dassault Systemes (France) provides a business platform for end-to-end continuity in shipbuilding and has acquired startups to strengthen its position as a system integrator [4] - SAP (Germany) focuses on enterprise application software and has expanded its offerings through acquisitions to optimize the shipyard work environment [5] - Accenture (Ireland) enhances digitalization practices globally and partnered with Hyundai Heavy Industries to build digital shipyards [6][7] Market Dynamics - Driver: Increasing use of Product Lifecycle Management (PLM) solutions improves collaboration, synchronization, and productivity in shipbuilding [8] - Opportunity: Augmented Reality (AR) can enhance efficiency in digital shipyards by providing immersive experiences and facilitating quality checks [9] - Challenge: The industry faces a stringent regulatory framework impacting various stakeholders including manufacturers, suppliers, and end customers [10]

Machine Learning Insights - The document shares tutorials and insights on Data Science (DS), Machine Learning (ML), Large Language Models (LLMs), and Retrieval Augmented Generation (RAGs) [1] - The document presents an explanation of "Kernel Trick" in the context of an ML interview question [1] Engagement & Networking - The author encourages readers to reshare the content [1] - The author shares their social media handle for further engagement [1]

机器学习面试准备 - 文档模拟机器学习面试场景 [1] - 面试问题聚焦于 Kernel Trick 的本质 [1] Kernel Trick 概念解析 - Kernel Trick 被称为 "Trick" 的原因分析 [1] - 提供 Kernel Trick 的数学解释 [1]

Core Insights - The article discusses the cost comparison between H100 and GB200 NVL72 servers, highlighting that the total upfront capital cost for GB200 NVL72 is approximately 1.6 to 1.7 times that of H100 per GPU [2][3] - It emphasizes that the operational costs of GB200 NVL72 are not significantly higher than H100, primarily due to the higher power consumption of GB200 NVL72 [4][5] - The total cost of ownership (TCO) for GB200 NVL72 is about 1.6 times higher than that of H100, indicating that GB200 NVL72 needs to be at least 1.6 times faster than H100 to be competitive in terms of performance/TCO [4][5] Cost Analysis - The price of H100 servers has decreased to around $190,000, while the total capital cost for a typical hyperscaler server setup can reach $250,866 [2][3] - For GB200 NVL72, the upfront capital cost per server is approximately $3,916,824, which includes additional costs for networking, storage, and other components [3] - The capital cost per GPU for H100 is $31,358, while for GB200 NVL72, it is $54,400, reflecting a significant difference in initial investment [3] Operational Costs - The operational cost per GPU per month for H100 is $249, while for GB200 NVL72, it is $359, indicating a smaller margin in operational expenses [4][5] - The electricity cost remains constant at $0.0870 per kWh across both systems, with a utilization rate of 80% and a Power Usage Effectiveness (PUE) of 1.35 [4][5] Recommendations for Nvidia - The article suggests that Nvidia should enhance its benchmarking efforts and increase transparency to benefit the machine learning community [6][7] - It recommends expanding benchmarking beyond NeMo-MegatronLM to include native PyTorch, as many users prefer this framework [8][9] - Nvidia is advised to improve diagnostic and debugging tools for the GB200 NVL72 backplane to enhance reliability and performance [9][10] Benchmarking Insights - The performance of training models like GPT-3 175B using H100 has shown improvements in throughput and efficiency over time, with significant gains attributed to software optimizations [11][12] - The article highlights the importance of scaling in training large models, noting that weak scaling can lead to performance drops as the number of GPUs increases [15][17] - It provides detailed performance metrics for various configurations, illustrating the relationship between GPU count and training efficiency [18][21]