e公司讯，DeepSeek效应持续发酵，机构认为将催化中国科技股价值重估。 美东时间周一，纳斯达克中国金龙指数涨2.61%，创4个月以来收盘新高，其中阿里巴巴涨7.55%。 同时，据证券时报记者梳理，2月10日收盘后至11日开盘前，已有多家A股上市公司通过官方微信等渠 道透漏相关业务最新进展： 长安汽车最新透漏，已完成Deepseek深度融合，2月12日行业首发量产搭载 上市；航天宏图天权大模型产品矩阵全面接入DeepSeek；广和通AI模组及解决方案全面支持DeepSeek- R1蒸馏模型；华胜天成智慧园区成功接入DeepSeek；利亚德·虚拟动点LYDIA动作大模型正式接入 DeepSeek；润建股份则最新透漏，已联合希姆计算采用自主研发AI芯片、编译器、工具链与DeepSeek 深度耦合，成功完成Deepseek-R1系列蒸馏模型的适配，发布DeepSeek加持全国产算力政务智能体一体 机。 ...

e公司讯，采访中记者了解到，除了云服务厂商，在硬件侧，当前已有超15家的芯片厂商适配了 DeepSeek模型，相关智算一体机也逐步落地；同时，多家手机、汽车企业也陆续宣布接入支持这一模 型，朋友圈持续"扩容"。 ...

国家高性能计算机工程技术研究中心副主任 曹振南：基于DeepSeek或者类似这样的开源、开放产品， 成本变低后整个应用面会急剧扩散，可能呈一个或者几个数量级的增长。 采访中记者了解到，除了云服务厂商，在硬件侧，当前已有超15家的芯片厂商适配了DeepSeek模型， 相关智算一体机也逐步落地；同时，多家手机、汽车企业也陆续宣布接入支持这一模型，朋友圈持 续"扩容"。 在硬件侧，连日来还有多家手机厂商和车企接连宣布，在自己的产品端接入了DeepSeek模型，可以直 接联网使用。采访中记者了解到，当前除了DeepSeek外，也有部分从业者在进行更小体量的人工智能 模型开发，以便未来能直接本地部署到端侧的手机、平板或汽车上。 记者注意到，这类端侧模型还能按照语音指示，直接让手机或车机在不同应用之间完成复杂任务操作， 比如导航到好友微信发的一个地址，或者是将车上观看的一个视频直接转发。企业负责人介绍，他们已 经在与业内厂商合作，这些场景年内都有望落地。 在北京一家国产智算芯片研发企业内，研发人员在春节后开工首日就宣布完成了对DeepSeek模型的适 配。企业负责人告诉记者，以往他们适配其他不开源的大模型时，需要与模型开 ...

业内人士认为，DeepSeek的面世有助于中小银行缩小与大型银行在大模型应用方面的差距。 大型银行在资源投入、生态系统构建及数据积累上的优势依然明显，中小银行在短期内难以赶超。 此外，银行在探索大模型应用之际，还面临着数据安全、隐私泄露、合规挑战、场景适应性不足等多重 风险。 因此，如何平衡技术进步与风险防控，已成为金融机构在运用人工智能技术过程中必须正视的议题。 e公司讯，"应用DeepSeek-VL2多模态模型，将信贷材料综合识别准确率提升至超97%，信贷审核全流程 效率提升了20%。 "苏商银行人士表示。 近日，多家银行成功本地化部署DeepSeek大模型，应用于智能合同管理、智能风控、资产托管与估值 对账、客服助手、智库等多个场景。 ...

星图云接入DeepSeek后，用户意图识别和逻辑推理能力整体提升10%，同时也为用户提供零代码开发的 智能体快速构建流程，提升空天信息行业垂类应用智能体构建效率30%。 e公司讯，据中科星图消息，星图云正式接入DeepSeek-R1大模型，服务再升级，为空天信息赋能千行百 业注入新的动力。 ...

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the impact of DeepSeek on the technology industry, particularly focusing on artificial intelligence (AI) and semiconductor sectors [1][2][10]. Core Insights and Arguments - **DeepSeek's Efficiency**: DeepSeek has exceeded expectations in efficiency, leading investors to question the necessity of ongoing AI investment. The narrative around AI is shifting towards better investment returns [1]. - **Adoption by Major Tech Companies**: Major tech firms are rapidly integrating DeepSeek into their AI offerings, with platforms like Meta, Azure, and AWS adopting these advancements [1][15]. - **Capital Expenditure Concerns**: There is a potential risk that increased adoption of DeepSeek may lead to reduced capital expenditures in AI hardware, which could impact profit margins and earnings [2][10]. - **Changing Perceptions of AI Investment**: The assumption that AI requires substantial capital investment for optimal performance is being challenged. Efficient models running on traditional GPUs may still be necessary, but the demand for high-end chips could be overstated [2][10]. - **Market Dynamics**: The semiconductor stocks are often revalued based on capital expenditure trends, and the current narrative suggests a potential downturn as companies reassess their AI spending [2][10]. - **Profitability Shift**: The profitability in the AI value chain may shift towards AI deployers (like software and cloud service providers) rather than hardware suppliers, as the latter face pressure from commoditization [9][22]. Additional Important Insights - **Open Source Models**: DeepSeek's open-source nature allows for lower-cost operations and integration, potentially disrupting the market for proprietary models [15][17]. - **Consumer Benefits**: Companies that utilize AI to enhance their competitive edge, such as cloud providers and software firms, are expected to benefit from reduced costs associated with AI deployment [22][12]. - **Risks for Hardware Suppliers**: Suppliers of AI hardware may face significant risks as their valuations have been adjusted upwards, creating higher thresholds for profitability [12][22]. - **Long-term vs. Short-term Dynamics**: The transition to more efficient AI models may create short-term gaps in demand for AI chips, but long-term innovations could drive down costs and increase adoption rates [18][20]. - **DeepSeek's Cost Efficiency**: DeepSeek's API is significantly cheaper than competitors, with a cost of $2.19 per million tokens compared to OpenAI's $60, indicating a potential shift in market dynamics [23]. Conclusion - The emergence of DeepSeek is reshaping the technology landscape, particularly in AI and semiconductors. While it presents opportunities for cost savings and efficiency, it also poses risks for traditional hardware suppliers and requires a reevaluation of capital expenditure strategies across the industry [1][2][9][12].

Summary of Key Points from the Conference Call Industry Overview - **Industry Focus**: Greater China Technology Semiconductors [85][88] - **Analyst Coverage**: Morgan Stanley's equity analysts covering the semiconductor sector in Asia Pacific include Charlie Chan, Daniel Yen, Daisy Dai, and Duan Liu [1][85]. Core Insights and Arguments - **Impact of DeepSeek on Technology**: The conference discussed how DeepSeek is expected to influence the technology landscape, particularly in AI and supply chain management [6][11]. - **Capex Growth Expectations**: A projected 29% growth in capital expenditures (capex) for 2025 was highlighted, driven by major players in the cloud sector including Alphabet, Amazon, Microsoft, and others [19][20]. - **NVIDIA Capex Growth**: Analysts noted differing assumptions regarding NVIDIA's capex growth for 2025, with various companies in the semiconductor supply chain expected to experience varying levels of growth [22]. - **Cloud Semiconductor Preferences**: The report recommended a preference for Montage Technology over Aspeed Technology based on earnings revision breadth and year-over-year share price performance [24][25]. - **Driver ICs Market Outlook**: The market leader in driver integrated circuits (ICs) is expected to outperform, with a healthy level of total AMOLED smartphone market share anticipated for Q1 2024 [27]. Risks and Valuation Methodology - **Valuation Methodology**: The valuation for Aspeed Technology and Montage Technology is based on a residual income model, with key assumptions including medium-term growth rates of 15.8% and 13.7% respectively [29][31]. - **Risks to Growth**: Upside risks include stronger cloud demand and faster-than-expected technology migration, while downside risks involve softening cloud demand and intensified competition from US peers [31][31]. Additional Important Information - **Investment Ratings**: The report includes various investment ratings for companies within the semiconductor sector, with a significant number rated as Overweight (O) [85][87]. - **Analyst Certifications**: Analysts certified that their views on the companies discussed are accurately expressed and have not received compensation for specific recommendations [36]. - **Disclosure of Conflicts**: Morgan Stanley disclosed potential conflicts of interest due to its business relationships with companies covered in the research [2][37]. This summary encapsulates the essential insights and data points from the conference call, providing a comprehensive overview of the semiconductor industry dynamics and investment outlook.

Summary of NVIDIA Corp. Conference Call Company Overview - **Company**: NVIDIA Corp. (Ticker: NVDA) - **Industry**: Semiconductors - **Market Cap**: $3,122.918 million - **Current Stock Price**: $124.83 - **Price Target**: $152.00 - **Fiscal Year Ending**: January 2024 Key Points and Arguments Industry Context - The sentiment around NVIDIA has worsened due to potential long-term risks associated with DeepSeek, but near-term business remains strong with increasing customer spending [1][3] - DeepSeek represents a significant evolutionary upgrade in the AI space, but it is one of many advancements in the past year [3][4] Financial Performance - EPS estimates for fiscal years are projected to grow from $1.30 in FY 2024 to $4.98 in FY 2027, indicating strong growth potential [7][57] - Revenue is expected to grow significantly, with projections of $128.866 billion in FY 2025 and $185.737 billion in FY 2026 [57] Risks and Challenges - Potential risks include further export controls, a changing financing environment for AI investments, and negative investor sentiment [5][13][14] - The government is expected to implement more restrictions, which could disrupt operations at the margin [11][12] - Investor sentiment has turned negative, which may not correlate with near-term results, but could impact revenue acceleration [14] Growth Drivers - Confidence in NVIDIA's Hopper and Blackwell architectures is building, with expectations of strong demand for both [10][15] - Large training clusters are still being built, indicating ongoing commitment from major customers despite market pressures [19] - Inference growth is expected to drive multiple years of growth, with NVIDIA maintaining a strong position in this market [20] Competitive Landscape - The market has recently favored ASIC over GPU solutions, but this trend is expected to reverse in the second half of 2025 as NVIDIA's GPU revenue accelerates [22] - NVIDIA's incumbency in training provides a competitive advantage, especially as GPUs can be repurposed for inference tasks [26] Market Sentiment and Pricing - Despite recent stock selloffs, pricing remains constructive, with unchanged list pricing across major cloud platforms [30] - Spot pricing for H100 GPUs has seen some regional increases, which is viewed positively for NVIDIA [31] Future Outlook - NVIDIA is expected to benefit from a strong ramp in Blackwell availability later in 2025, enhancing its competitive position [52] - The company is well-positioned to capitalize on growth in AI/ML hardware solutions, with incremental opportunities in software and services [52][63] Additional Important Insights - NVIDIA's stock is rated as "Overweight" by Morgan Stanley, reflecting confidence in its growth trajectory and market position [46][54] - The company is expected to trade at a premium due to its higher exposure to AI, with a projected revenue growth of 44.1% in 2025 [51][52] This summary encapsulates the key insights from the conference call, highlighting NVIDIA's current market position, growth potential, risks, and competitive landscape.

Summary of the Conference Call on China Technology and AI Landscape Industry Overview - The report focuses on the AI landscape in China, highlighting the significant cost advantages of AI inference in China compared to the US, which could lead to wider adoption once a compelling use case is identified [1][2][3] Key Developments in AI Models - Major Chinese tech companies such as Alibaba (BABA), ByteDance, Tencent, and startups like MiniMax and Moonshot AI have made substantial advancements in AI models since the last update in September 2024 [2] - Chinese AI players have narrowed the gap with US counterparts through innovative techniques and fine-tuning existing models [2] Cost Advantages - The cost of adopting AI in China is approximately 80% cheaper than in the US, with ByteDance's model showing input and output costs at 4% and 3% of OpenAI's GPT-4o costs, respectively [3] - Despite lower costs, many Chinese AI companies are not prioritizing monetization in the near term [3] Innovations and Techniques - DeepSeek's R1 model has shared its training techniques publicly, which may accelerate global AI model development [4] - The commercial value of AI is expected to depend on discovering a "killer use case" [5] - The report emphasizes the importance of model efficiency, particularly through the Mixture-of-Experts (MoE) framework and reinforcement learning (RL) [11] Performance Comparisons - Recent models from Chinese companies have shown competitive performance against leading global models like GPT-4o and Claude-3.5-Sonnet [18] - ByteDance's Doubao-1.5-pro is noted for its efficiency, outperforming several benchmarks while maintaining low costs [26][29] Consumer Applications and Market Dynamics - Consumer AI applications in China are still in early stages, with no dominant "killer app" emerging yet [44] - ByteDance's Doubao leads the AI chatbot market with 75 million monthly active users (MAUs), significantly outperforming competitors [45] - User engagement metrics indicate a growing interest, with Doubao showing a notable improvement in user retention [46] Company-Specific Innovations Alibaba - Launched Qwen2.5-Max, which claims to outperform DeepSeek V3 and GPT-4o in some benchmarks, with a training cost of approximately $12 million [25] - Focused on enhancing model safety and alignment through extensive human evaluations [21] ByteDance - Released Doubao-1.5-pro, achieving a 7x efficiency leverage and maintaining a gross margin of 50% [26][27] - Plans to invest $12 billion in AI infrastructure in 2025 [27] Moonshot AI - Introduced Kimi k1.5, emphasizing long-context scaling and multimodal capabilities [28] - Achieved significant performance improvements in reasoning tasks [34] MiniMax - Launched MiniMax-01, focusing on expanding context windows and employing linear attention for efficiency [31][32] - Open-sourced its models to enhance collaboration and innovation [31] Tencent - Released Hunyuan large, which outperforms several benchmarks and introduced multimodal capabilities with Hunyuan3D 2.0 and HunyuanVideo [33][39] Baidu - Plans to unveil the next generation of its ERNIE model in early 2025, with significant improvements in performance [39] Conclusion - The Chinese AI landscape is rapidly evolving, with significant advancements in model efficiency and cost-effectiveness. However, the market for consumer applications remains nascent, and the search for a breakthrough use case continues. The competitive dynamics among leading Chinese firms indicate a strong push towards innovation and market leadership in the global AI arena.

Summary of Key Points from DeepSeek Conference Call Industry and Company Involved - **Industry**: AI and Technology Sector - **Company**: DeepSeek Core Insights and Arguments - **Impact on Global Capital Markets**: DeepSeek's release has generated significant reactions in global capital markets, with many large enterprises, such as Google, increasing their capital expenditure expectations by 20%-30% compared to previous forecasts [2][4] - **DeepSeek V3 Model**: The model utilizes MOE (Mixture of Experts) and multi-head attention mechanisms, reducing training and inference costs, thus accelerating AI application development and narrowing the gap between domestic and overseas models [2][16] - **Data Center and Server Demand**: The data center and server industry is expected to benefit significantly from DeepSeek, as AI applications increase demand for these services, leading to growth in private cloud development [2][5] - **SaaS Industry Opportunities**: The SaaS sector presents notable investment opportunities, with companies like Xiaomi, Huawei, and ByteDance actively advancing their cloud businesses [6] - **Animation Film Industry**: The animation film industry is projected to have significant investment opportunities in 2025, with several major releases expected to drive market growth [2][27] - **Investment Strategy**: Emphasis on investing in core leading companies that are closely linked to DeepSeek and future large models, with recommendations for companies like Haiguang Information and Kingsoft [10][11] Other Important but Possibly Overlooked Content - **AI Applications in Media**: There are various investment opportunities in the media sector, including AR toys, AI marketing, and AI-enhanced films, with specific companies highlighted for their potential [26][29] - **End-Side AI Penetration**: Increased penetration of AI in end-user devices like smartphones and PCs is expected to create growth opportunities in hardware markets, benefiting companies like Apple and various Android manufacturers [23][25] - **Market Environment and Timing**: The current market environment shows signs of a turnaround, with public funds historically underweight in the computer sector, indicating potential for increased allocations [11][12] - **Core Enterprises in Optical Module and IDC**: Key players in the optical module industry include Guangxun Technology and Huagong Technology, while IDC segment leaders include Runze Technology and Huayun [21][22] This summary encapsulates the essential insights and implications from the conference call regarding DeepSeek's influence on various sectors and investment strategies.