July 7, 2025 07:58 PM GMT Investor Presentation | Asia Pacific Tuesday TMT Webcast: China's AI Semi Development in a Global Context; TSMC Preview | M | | | | --- | --- | --- | | | | Update | | July 7, 2025 07:58 PM GMT | | | | Investor Presentation Asia Pacific | Morgan Stanley Taiwan Limited+ | | | | Charlie Chan | | | | Equity Analyst Charlie.Chan@morganstanley.com | +886 2 2730-1725 | | Tuesday TMT Webcast: China's | Daniel Yen, CFA | | | | Equity Analyst | | | AI Semi Development in a | Daniel.Yen@morga ...

Investment Rating - Industry View: In-Line [5] Core Insights - The semiconductor industry is experiencing unprecedented demand driven by AI advancements and geopolitical tensions [3][5] - China's AI semiconductor market is expected to see significant growth, with local GPU revenue projected to reach Rmb287 billion by 2027 [21][19] - The overall AI semiconductor market is anticipated to deliver over 30% CAGR from 2023 to 2030, with inference AI semiconductors growing at 55% CAGR [78][77] Summary by Sections China AI Semi Demand and Supply - The top six companies' capital expenditures are forecasted to grow 62% YoY to Rmb373 billion [10] - China's GPU self-sufficiency ratio was 34% in 2024 and is expected to reach 82% by 2027 [16] - The total addressable market (TAM) for China's cloud AI is projected to be US$48 billion by 2027 [18] Semiconductor Solutions and Technology Trends - Moore's Law is expected to continue with chip scaling to 3nm/2nm for better power efficiency [78] - Advanced packaging technologies like CoWoS and SoIC are being utilized to increase data speed and memory bandwidth [78] - The EDA market in China is projected to grow at a 12% CAGR from 2023 to 2030, reaching US$3.3 billion [29] Investment Opportunities - AI semiconductors are expected to account for approximately 34% of TSMC's revenue by 2027 [148] - The demand for custom AI semiconductors is increasing, driven by major cloud service providers and tech companies [120][121] - The global semiconductor market size may reach US$1 trillion by 2030, with AI semiconductors being a major growth driver [59]

In this articleNVDA"Compared to Nvidia's export-restricted chips, the performance gap between Huawei and the H20 is less than a full generation," said Dylan Patel, founder, CEO and chief analyst of SemiAnalysis. Sinology | Moment | Getty ImagesWith the U.S. restricting China from buying advanced semiconductors used in artificial intelligence development, Beijing is placing hopes on domestic alternatives such as Huawei. The task has been made more challenging by the fact that U.S. curbs not only inhibit Chin ...

Investor Presentation | Asia Pacific Asia Summer School: Tech Diffusion: Global AI Semi Demand and Supply Chain June 9, 2025 09:33 AM GMT As AI reshapes our daily life, the semiconductor industry faces unprecedented demand and even geopolitical tensions. In this session, we will provide an overview of the evolving global AI semi market, including the critical dynamics of the supply chain and China's accelerated AI localization push. | M | Charlie Chan | Foundation | | --- | --- | --- | | June 9, 2025 09:33 ...

Core Insights - The article discusses the concept of "Sputnik Moment" in various sectors, particularly focusing on the need for a similar moment in Chinese consumer confidence, which has been lacking despite advancements in other industries [1][14]. Group 1: Biotechnology and Pharmaceuticals - CanSino Biologics' PD-1/VEGF dual antibody "Yivolumab" achieved a significant milestone by outperforming the global leader "K drug" in clinical trials, marking a leading position for China in the dual antibody sector [5]. - The proportion of large pharmaceutical companies engaging in significant transactions with Chinese biotech firms has surged from less than 5% before 2019 to 31% in 2024, indicating a growing recognition of China's biotech capabilities [6]. Group 2: Aerospace and Defense - China successfully conducted test flights of two sixth-generation fighter jets on December 26, 2024, marking a significant breakthrough in global aviation technology and establishing China as the first country to achieve this feat [7][8]. - The successful test flights signify a new phase in the competition for air combat dominance, with advanced features such as all-aspect stealth and AI integration [7][8]. Group 3: Artificial Intelligence - DeepSeek's R1 model achieved performance comparable to OpenAI's GPT-3 at a fraction of the training cost, leading to a significant drop in Nvidia's stock price and highlighting a pivotal moment in the AI sector [9]. - The advancements in AI technology from Chinese companies are prompting a reevaluation of strategies in the U.S. tech landscape, as noted by prominent venture capitalists [9]. Group 4: Automotive Industry - In 2024, China exported nearly 6 million vehicles, significantly outpacing Japan's 4 million, with BYD emerging as the largest brand for pure electric vehicles globally [10][11]. - The automotive sector is undergoing rapid changes, with Chinese brands like BYD and Geely ranking among the top ten global automotive brands, reflecting a shift in market dynamics [11]. Group 5: Consumer Confidence and Economic Challenges - Consumer confidence in China has been declining, with significant increases in household savings and deflationary pressures observed [3][14]. - The decline in consumer confidence can be traced back to several factors, including geopolitical tensions, the real estate crisis, and the impact of COVID-19 lockdowns [15][18][20]. - The article emphasizes the need for measures to stabilize the real estate market and enhance consumer confidence to stimulate domestic consumption [24][25].

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]

今天大家都在谈MS的这篇DeepSeek R2分析的报告，提前曝光了R2的性能和参数，我们简单总结一 下这个报告的核心内容： DeepSeek R2 使用了多达 1.2 万亿个参数，采用了新颖的架构，实现了运行成本的显著降低。其采用 混合专家混合（MoE）架构，有 780 亿个活跃参数。 并且R2 使用华为的 Ascend 910B 芯片进行训练，而非 NVIDIA 的芯片。 R2 增强了多语言覆盖能 力，能流畅处理非英语语言；扩展了强化学习，利用更大的数据集，使模型能够进行更具逻辑性和 更像人类的推理；增加了多模态功能，能够处理文本、图像、语音和视频数据；实现了推理时的缩 放，通过采用通用奖励模型（GRM），在推理过程中增加计算资源，从而提高了输出质量。 R2 具有高成本效益，输入成本为每百万代币 0.07 美元，输出成本为每百万代币 0.27 美元，而 R1 的 输入成本为 0.15-0.16 美元，输出成本为 2.19 美元。 由于这篇报告讲的人已经很多了，我们就不赘述了，而且报告也放到了星球中，有兴趣的朋友可以 到星球中看原文。 今天这篇文章来看另一篇AI的分析，Artificial Analysis ...

Core Insights - The report on DeepSeek R2 highlights its significant advancements in performance and cost efficiency, utilizing a novel architecture with 1.2 trillion parameters and a mixture of experts (MoE) framework [1] - The report from Artificial Analysis outlines six major trends in the AI sector expected by early 2025, focusing on advancements in intelligence, efficiency, and multimodal capabilities [2] Group 1: AI Progress - The AI industry continues to make strides in model intelligence, cost efficiency, and speed, with leading labs like OpenAI, Google, and xAI at the forefront [3] - OpenAI's o4-mini and o3 models lead in intelligence, followed by Google's Gemini 2.5 Pro and xAI's Grok 3, indicating a competitive landscape with rapid innovation [3] - OpenAI and Google maintain a competitive edge through vertical integration in the AI value chain, while smaller players focus on specific modalities [3] Group 2: Rise of Chinese AI - Chinese AI labs, such as DeepSeek and Alibaba, have made significant progress in open-weight models, narrowing the gap with U.S. labs and enhancing China's influence in the open AI ecosystem [4] Group 3: Reasoning Models - Reasoning models that generate intermediate tokens before answering have significantly improved intelligence levels, outperforming non-reasoning models in various assessments [5] - Google’s Gemini 2.5 Pro exemplifies this advancement by correctly answering complex problems, while non-reasoning models prioritize speed and cost [5] Group 4: AI Agents - AI systems are increasingly capable of autonomously completing end-to-end tasks by chaining requests from multiple large language models (LLMs), enhancing their practicality [6] Group 5: Efficiency and MoE - The report emphasizes that advancements in small model intelligence, reasoning efficiency, and next-generation hardware have led to a significant reduction in inference costs [7] - MoE models activate only a portion of parameters during inference, contributing to improved efficiency and accessibility of high-performance AI [7] Group 6: Multimodal AI - Multimodal AI has made substantial progress, with advancements in image generation, video generation, and speech processing [8][9] - OpenAI's GPT-40 sets a new standard in image generation quality, while Google’s Veo 2 surpasses OpenAI's Sora in video generation [8] - Speech-to-text and text-to-speech models have also improved, with OpenAI and ElevenLabs leading in accuracy [9] Group 7: Open-Weight Models and Competitive Landscape - Open-weight models from Alibaba, DeepSeek, Meta, and NVIDIA have significantly closed the intelligence gap with proprietary models, although OpenAI's o4-mini and Google's Gemini 2.5 Pro still hold slight advantages [14] - The AI landscape is becoming increasingly crowded, with competition among U.S. labs and companies like NVIDIA, DeepSeek, and Alibaba intensifying [14]

Guidance on Application of General Prohibition 10 (GP10) to People's Republic of China (PRC) Advanced-Computing Integrated Circuits (ICs) APPLICABLE REGULATIONS May 13, 2025 SUMMARY This guidance alerts industry to the risks of using PRC advanced-computing ICs, including specific Huawei Ascend chips. These chips were likely developed or produced in violation of U.S. export controls. BIS is warning that, pursuant to GP10, the use of such PRC advanced- computing ICs risks violating U.S. export controls and ma ...