Core Insights - BluSky AI Inc. has launched the SkyMod series, a modular AI datacenter infrastructure designed for both indoor and outdoor deployment, emphasizing innovation and scalability [1][4][9] Product Overview - The flagship SkyMod One is a one-megawatt unit with a footprint of approximately 1,400 square feet, while the SkyMod XL offers a capacity of 1.7 MW and covers 3,000 square feet, both featuring rapid deployment capabilities [2] - The SkyMod series integrates NVIDIA GPUs, marking a significant advancement in high-performance AI infrastructure [3] Strategic Vision - The modular design of SkyMod allows for agile infrastructure that adapts in real-time to AI innovations, enabling clients to focus on product development and research rather than infrastructure challenges [4][5] - Each SkyMod is fully assembled and tested in a facility before being shipped, ensuring readiness for immediate deployment [6] Sustainability Commitment - Sustainability is central to BluSky's design philosophy, with efficient cooling and power systems that reduce operational costs and environmental impact, aligning with corporate ESG goals [7] Market Positioning - SkyMod units are available for deployment to partner institutions, enterprise clients, and research facilities, supporting a range of AI workloads from generative AI to GPU-as-a-service platforms [7][9] - BluSky AI aims to address the global AI supply shortage with innovative, turnkey modular solutions, transforming how AI companies access necessary compute power [9]

Core Insights - Nebius and Saturn Cloud have launched a first-in-class AI MLOps cloud solution that integrates NVIDIA Hopper GPUs and the NVIDIA AI Enterprise software stack, providing a comprehensive infrastructure for AI/ML engineers [1][6][10] Group 1: Product Offering - The new solution combines Nebius's AI cloud capabilities with Saturn Cloud's MLOps platform, allowing users to instantly access Jupyter notebooks and manage cloud resources on NVIDIA Hopper GPUs [2][4] - The service is offered at a significantly lower cost compared to traditional cloud service providers, making it an attractive option for various use cases [2][5] - Organizations can deploy enterprise-grade applications in a Nebius virtual private cloud environment, ensuring compliance with IT security standards and access to cost-efficient GPUs [3][6] Group 2: User Accessibility - Individuals and teams can join over 100,000 users of Saturn Cloud's hosted tiers, enabling quick sign-up and deployment of cloud resources with competitive pricing [4][5] - The solution allows teams to leverage Nebius's AI Cloud without the need for long-term investments in computing systems, with options for capacity reservations to enhance cost savings [5][6] Group 3: Strategic Impact - The collaboration aims to democratize access to enterprise-grade AI capabilities for organizations of all sizes, enabling them to become AI-driven without significant financial or engineering investments [6][7] - The integration of NVIDIA AI Enterprise software enhances Saturn Cloud's MLOps platform, providing advanced tools for AI development and deployment [6][10] Group 4: Company Background - Nebius is a technology company focused on building full-stack cloud infrastructure for the global AI industry, with a presence in Europe, North America, and Israel [9][10] - Saturn Cloud is recognized as the only MLOps platform offering multi-cloud GPU access on demand, simplifying the management of machine learning models at scale [10]

Investment Rating - Industry View: In-Line [7] Core Insights - The semiconductor industry is experiencing unprecedented demand driven by AI advancements and geopolitical tensions, particularly in the context of China's push for AI localization [4][8]. - The report highlights a decoupling between broader semiconductor cycles and AI growth, indicating that while overall semiconductor growth was slow at 10% year-over-year in 2024, AI-related demand continues to surge [10][13]. - Logic semiconductor foundry utilization is reported at 70-80% in the first half of 2025, suggesting that recovery is still ongoing [9]. Demand and Supply Dynamics - Significant demand is anticipated from AI, with NVIDIA experiencing booming demand and its Days of Inventory (DOI) reaching a historical low [15]. - The report forecasts that the top six companies' capital expenditures (capex) will grow by 62% year-over-year to RMB 373 billion [30]. - China's GPU self-sufficiency ratio was 34% in 2024, expected to rise to 82% by 2027, with local GPU revenue projected to reach RMB 287 billion by 2027 [32][35]. Market Trends and Projections - The total addressable market (TAM) for cloud AI semiconductors is projected to grow to USD 235 billion in 2025, with edge AI semiconductors expected to grow at a compound annual growth rate (CAGR) of 22% from 2023 to 2030 [49][60]. - Inference AI semiconductors are forecasted to grow at a CAGR of 55% from 2023 to 2030, outpacing training and general-purpose chips [60]. - The report anticipates robust cloud capex spending of nearly USD 789 billion across 2025-2026, driven by major cloud service providers [49]. Supply Chain and Capacity - TSMC is expected to expand its CoWoS capacity significantly, with projections of producing 5.1 million chips in 2025 [61][70]. - AI computing wafer consumption is estimated to reach up to USD 15 billion in 2025, with NVIDIA accounting for the majority of this consumption [73]. - The report indicates that the semiconductor supply chain is under pressure, with GPU supply and demand needing time to align [70].

Investment Rating - The industry investment rating is "Strongly Outperforming the Market," indicating an expected industry index increase of over 5% in the next six months [59]. Core Insights - The AI sector is witnessing accelerated implementation across various stages, countering market pessimism regarding macroeconomic and policy uncertainties. Major tech companies in the US continue to invest in AI capital and commercial applications, reinforcing the AI narrative [4]. - The annualized revenue run rate for Kuaishou's Keling AI has surpassed $100 million, marking a significant milestone in China's AI commercialization journey [7][35]. Summary by Sections Global AI Dynamics - Broadcom's Q2 revenue reached $15 billion, a 20% year-on-year increase, with AI-related semiconductor revenue growing by 46% to $4.4 billion, significantly exceeding expectations [4][15]. - MongoDB's Q1 revenue grew by 22% year-on-year, with its core Atlas business increasing by 26%, benefiting from its versatility in data infrastructure and AI model integration [4][27]. - CrowdStrike's annual recurring revenue (ARR) exceeded $4.4 billion, with a 22% year-on-year growth, driven by its subscription model and AI innovations [6][10]. Key Company Performance - Kuaishou's Keling AI achieved an annualized revenue run rate of over $100 million within ten months of launch, with significant monthly revenue contributions in April and May [7][35]. - Rubrik's Q1 performance showed an ARR of $1.2 billion, with a net retention rate exceeding 120%, reflecting strong growth momentum driven by AI capabilities [4][21]. - OpenAI's ChatGPT received significant updates, enhancing its integration with common tools and introducing a meeting recording feature, thereby improving user efficiency [4][40]. Investment Recommendations - The report suggests focusing on key beneficiaries in the AI infrastructure space, including Broadcom, NVIDIA, and Vertiv, due to their strong performance and growth potential [4]. - For AI application companies, MongoDB, Rubrik, Salesforce, and Snowflake are highlighted as having robust growth prospects driven by their platform capabilities and AI integration [4].

Robotics Technology & Development - Boston Dynamics' Atlas robot showcases advancements in perception, enabling it to identify objects and navigate dynamic environments [1][3][4] - Atlas utilizes a vision system with cameras and overlaid red/green points to perceive its surroundings, identify objects, and avoid hazards [3][4] - The robot constructs both 2D and 3D models of its environment to determine object distance and orientation [4] - Atlas combines vision system data with joint information to track object positions, even when visibility is obstructed [5] - The robot compares objects to 3D models from its training to determine their pose, location, and optimal gripping method [5] - The robotics industry is shifting towards generalized robot training, enabling robots to perform various tasks from a single training type [1][6] - NVIDIA's Dextra RGB workflow facilitates fully autonomous robot training in simulation before real-world application [6] Industry Trends - The robotics industry is moving away from task-specific training towards more versatile, generalized training methods [1][6]

Group 1: Foreign Exchange and Gold Reserves - As of May 2025, China's foreign exchange reserves reached $32,853 billion, an increase of $36 billion from April, representing a growth rate of 0.11% [1] - By the end of May, China's gold reserves stood at 7,383 million ounces (approximately 2,296.37 tons), with a month-on-month increase of 60,000 ounces (about 1.86 tons), marking the seventh consecutive month of gold accumulation [1] Group 2: A-Share Market Analysis - After the "fill the pit" market phase, A-shares are expected to experience a strong upward trend driven by policies, external events, industry rotation, and market sentiment [2][3] - Historical data shows that after seven instances of rapid declines followed by rebounds since 2015, the average duration of subsequent market fluctuations lasted 86 trading days, with five out of seven instances leading to price increases [2] - Current positive policies and external events, including a recent call between the leaders of China and the U.S., have reduced concerns regarding U.S.-China tensions, contributing to a favorable market outlook [3] Group 3: Economic Indicators - Industrial profits for large-scale enterprises grew by 3% year-on-year in April, with a cumulative growth of 1.4% from January to April, indicating a continued positive trend [5] - The manufacturing PMI for May rose to 49.5%, reflecting an improvement in manufacturing activity, with production indices exceeding the critical threshold [5][6] - The market remains cautious about the impact of U.S. tariffs, but the overall economic indicators suggest a supportive environment for market stability [6] Group 4: Industry Configuration and Investment Recommendations - Short-term investment strategies should focus on technology, new consumption, and undervalued blue-chip stocks, with an emphasis on sectors like computing, communication, and innovative pharmaceuticals [4] - The technology and advanced manufacturing sectors are highlighted as key areas for investment, supported by ongoing policy initiatives and market trends [6] - Companies in the U.S. and Hong Kong, such as Circle and Coinbase, as well as A-share companies like Sifang Jingchuang and Zhongke Jincai, are identified as potential investment targets in the context of stablecoins and RWA [7][9] Group 5: NVIDIA's Robotics Ecosystem - NVIDIA is focused on developing platforms and tools for robotics, emphasizing the creation of a foundational development ecosystem [10] - The company has introduced a comprehensive solution for robotics that integrates training, optimization, and execution through its various computing platforms [11][12] - Investment recommendations include companies involved in automotive robotics, such as Top Group and Bertly, which are expected to benefit from NVIDIA's advancements in the robotics sector [13]

Investment Rating - The semiconductor production equipment industry is rated as Attractive [5][70]. Core Insights - The imminent launch of DeepSeek R2, which features 1.2 trillion parameters and significant cost efficiencies, is expected to positively impact the Japanese semiconductor production equipment (SPE) industry [3][7][11]. - The R2 model's capabilities include enhanced multilingual support, broader reinforcement learning, multi-modal functionalities, and improved inference-time scaling, which could democratize access to high-performance AI models [7][9][11]. - The development of efficient AI models like R2 is anticipated to increase demand for AI-related SPE, benefiting companies such as DISCO and Advantest [11]. Summary by Sections DeepSeek R2 Launch - DeepSeek's R2 model is reported to have 1.2 trillion parameters, a significant increase from R1's 671 billion parameters, and utilizes a hybrid Mixture-of-Experts architecture [3][7]. - The R2 model offers cost efficiencies with input costs at $0.07 per million tokens and output costs at $0.27 per million tokens, compared to R1's $0.15-0.16 and $2.19 respectively [3][7]. Industry Implications - The launch of R2 is expected to broaden the use of generative AI, leading to increased demand for AI-related SPE across the supply chain, including devices like dicers, grinders, and testers [11]. - The report reiterates an Overweight rating on DISCO and Advantest, which are positioned to benefit from the anticipated increase in demand for AI-related devices [11]. Company Ratings - DISCO (6146.T) is rated Overweight with a target P/E of 25.1x [12]. - Advantest (6857.T) is also rated Overweight, with a target P/E of 14.0x [15].

Investment Rating - The semiconductor production equipment industry is rated as Attractive [5] Core Insights - The imminent launch of DeepSeek R2, which features 1.2 trillion parameters and significant cost efficiencies, is expected to positively impact the Japanese semiconductor production equipment (SPE) industry [3][7] - The development of lightweight, high-performing AI models like DeepSeek R2 is anticipated to democratize access to generative AI, thereby expanding the market for AI-related SPE [11] Summary by Sections DeepSeek R2 Characteristics - DeepSeek R2 is reported to have 1.2 trillion parameters, with 78 billion active parameters and utilizes a hybrid Mixture-of-Experts architecture [3] - The input cost for R2 is $0.07 per million tokens, significantly lower than R1's $0.15-0.16, while the output cost is $0.27 compared to R1's $2.19 [3][7] - Enhanced multilingual capabilities and broader reinforcement learning are key upgrades in R2, allowing it to handle various data types including text, image, voice, and video [9][11] Market Implications - The anticipated launch of R2 is expected to boost demand for AI-related devices, including GPU and HBM, as well as custom chips and other AI devices [11] - The report reiterates an Overweight rating on DISCO and Advantest, which are expected to benefit from increased demand for AI-related devices [7][11] Company Ratings - Advantest (6857.T) is rated Overweight with a target price of ¥10,300 based on expected earnings peak [16] - DISCO (6146.T) is also rated Overweight with a target P/E of 25.1x based on earnings estimates [13]

Core Insights - CoreWeave, in collaboration with NVIDIA and IBM, achieved a significant milestone by delivering the largest-ever MLPerf® Training v5.0 submission using 2,496 NVIDIA Blackwell GPUs, marking a 34x larger scale than the next largest submission from a cloud provider [1][2] - The submission completed the training of the Llama 3.1 405B model in just 27.3 minutes, demonstrating over 2x faster training performance compared to other similar cluster submissions, showcasing the capabilities of the GB200 NVL72 architecture [2][3] - CoreWeave's cloud platform is designed to meet the demands of AI workloads, enabling faster model development cycles and optimized Total Cost of Ownership, effectively cutting training time in half for its customers [3] Company Overview - CoreWeave, known as the AI Hyperscaler™, provides a cloud platform that supports accelerated computing for enterprises and AI labs, with a growing presence of data centers across the US and Europe since its inception in 2017 [4] - The company has been recognized as one of the TIME100 most influential companies and featured in the Forbes Cloud 100 ranking in 2024, highlighting its impact and leadership in the cloud computing space [4]

Summary of Conference Call on Taiwan Technology: Semiconductors Industry Overview - The semiconductor industry is experiencing a shift towards more complex chip designs, particularly in the AI and High-Performance Computing (HPC) segments, which is driving demand for advanced chip testing [1][11][58]. - The probe card and socket markets are projected to grow steadily, with the probe card market reaching US$2.5 billion and the socket market reaching US$1.6 billion in 2024, representing approximately 17% and 11% of the total testing equipment market, respectively [52]. Key Companies MPI (6223.TWO) - MPI is ranked as the 4th largest probe card provider globally, with 57% of its revenue in 2024 derived from probe cards [10][52]. - The company is expected to achieve a revenue CAGR of 19% from 2024 to 2027, driven by increased demand in the AI/HPC segments [14][33]. - MPI's market share in the probe card market is projected to rise from 7% in 2024 to 11% by 2027 [13]. WinWay (6515.TW) - WinWay is the 2nd largest socket provider globally, generating 71% of its revenue from test and burn-in sockets [10][52]. - The company is expected to see a revenue CAGR of 23% from 2024 to 2027, benefiting from its expansion into the probe card market [14][37]. - WinWay's market share in the socket market is expected to increase from 8% in 2024 to 14% by 2027 [13]. Investment Opportunities - Both MPI and WinWay are initiated with a Buy rating and target prices of NT$1,000 and NT$1,500, respectively, implying potential upsides of approximately 41% and 54% [3][16]. - The investment thesis is supported by: 1. Increasing dollar content in the testing industry due to AI and HPC trends, leading to a doubling of average selling prices (ASPs) for probe cards and sockets [3][11][59]. 2. Local advantages for Taiwanese vendors, including proximity to leading foundries like TSMC and OSAT companies, which are expected to enhance market share [13][12]. 3. Expansion into new markets, particularly in high-margin segments like MEMS probe cards for MPI and probe cards for WinWay [14][58]. Financial Performance - MPI's earnings are forecasted to grow at a CAGR of 28% from 2024 to 2027, while WinWay's earnings are expected to grow at a CAGR of 37% during the same period [39][41]. - MPI's 2024 revenue is projected at NT$10.17 billion, with net income expected to reach NT$2.30 billion [10][33]. - WinWay's 2024 revenue is projected at NT$5.80 billion, with net income expected to reach NT$1.19 billion [18][37]. Risks - Potential downside risks include softer demand in AI and HPC markets, slower penetration into new total addressable markets (TAM), and intensifying competition [4]. Conclusion - The semiconductor testing industry, particularly for advanced chip testing, is poised for significant growth driven by increasing complexity in chip designs and the demand for faster time to market. MPI and WinWay are well-positioned to capitalize on these trends, making them attractive investment opportunities despite current market volatility.