Core Viewpoint - DeepSeek has made significant advancements in the open-source model space with the release of its upgraded R1 inference model (0528), which shows competitive performance against proprietary models [2][4][10]. Performance Summary - The R1-0528 model has improved benchmark performance, enhancing front-end functionality, reducing hallucinations, and supporting JSON output and function calls [3]. - In the latest performance rankings from LMArena, DeepSeek-R1 (0528) achieved an overall ranking of 6th, and it is the top-ranked open model [5][4]. - Specific rankings in various categories include: - 4th in Hard Prompt testing - 2nd in Coding testing - 5th in Math testing - 6th in Creative Writing testing - 9th in Instruction Following testing - 8th in Longer Query testing - 7th in Multi-Turn testing [6][7]. Competitive Landscape - In the WebDev Arena platform, DeepSeek-R1 (0528) is tied for first place with other proprietary models like Gemini-2.5-Pro-Preview-06-05 and Claude Opus 4, surpassing Claude Opus 4 in score [8]. - The performance of DeepSeek-R1 (0528) is seen as a milestone, particularly in the AI programming domain, where it competes closely with established models like Claude [10]. User Engagement - The strong performance of DeepSeek-R1 (0528) has generated increased interest and usage among users, prompting discussions about user experiences [9][11].

Core Viewpoint - The sentiment of foreign investors towards the Chinese market is improving, with a focus on the recovery of the domestic economy and the ongoing dynamics of Sino-U.S. relations [1][4]. Group 1: Structural Improvement in the Stock Market - Since the second half of 2024, the Chinese stock market has been experiencing structural improvements, driven by a rebound in ROE and the rise of new technology sectors [4]. - Domestic leading companies are demonstrating operational resilience and growth momentum through measures such as shareholder returns, stock buybacks, and moderate leverage, contributing to sustainable ROE recovery and valuation uplift [4]. - Global investors express a willingness to increase their allocation to Chinese stocks, acknowledging that their current allocation is 2.4 percentage points below the MSCI Emerging Markets benchmark, indicating potential for increased investment [4][6]. Group 2: Interest in AI and Technology - Foreign investors are increasingly interested in AI, technology-related themes, and new consumption trends, recognizing missed opportunities in China's technological advancements since 2021-2022 [6]. - Concerns about China's competitiveness in global technology have shifted, with breakthroughs in AI and advancements in electric vehicles and robotics prompting a reevaluation of investment strategies [6]. Group 3: Key Topics of Interest - The recovery of the domestic economy remains a focal point for foreign investment banks, with challenges to sustainable growth still present [9]. - Catalysts for market observation include fiscal policy timing and scale, export resilience, real estate market stabilization, and the evolution of Sino-U.S. tariffs [10][12]. - The divergence between A-shares and H-shares is of interest, attributed to differences in industry composition and the concentration of high-ROE sectors in the Hong Kong market [12]. Group 4: Investment Strategy Consensus - In the context of structural improvements in the Chinese stock market and the clear intent of foreign investors to increase allocations, a balanced approach with selective stock picking is a common consensus among institutions [15].

Investment Rating - The report reiterates a Buy rating on SK Hynix and Samsung Electronics due to expected demand growth in the DRAM market driven by GDDR7 and LPDDR5X [1][6]. Core Insights - The global memory supply shortage is anticipated to intensify in the second half of 2025, primarily due to rising demand for GDDR7 driven by advancements in AI inference models and edge AI devices [1][5]. - GDDR7 is expected to significantly enhance performance with a 2x increase in data rates, reaching 4.8Gbps per pin, and doubling bandwidth capacity to 192GB/s per device [2]. - The demand for GDDR7 is projected to contribute an additional 4.03 billion Gb to global DRAM demand in 2H25, representing a 24% increase in graphic DRAM demand and a 2.4% increase in overall global DRAM demand [4][7]. Summary by Sections GDDR7 Technology - GDDR7 features advanced PAM3 technology, improving data density by 50% per clock cycle compared to GDDR6, while operating at a lower voltage of 1.1-1.2V [2]. - The architecture of GDDR7 utilizes four 8-bit channels, enhancing parallel processing capabilities and reducing latency for AI workloads [2]. AI Inference Demand - The emergence of AI distillation technology is expected to drive significant memory demand for AI inference, leading to increased adoption of GDDR7 as an alternative to HBM [3]. Market Projections - The report projects GPU demand from DeepSeek to reach 2 million units in 2H25, with each GPU requiring 96GB of DRAM, contributing to the overall demand increase [4]. - The anticipated DRAM content upgrade in Apple's iPhone 17 series is expected to add an additional 3.2% to global DRAM demand in 2H25 [4].

Investment Rating - The report provides a cautious outlook on the technology sector in Asia Pacific, particularly focusing on the developments surrounding DeepSeek's R2 model [7]. Core Insights - DeepSeek's R2 model is anticipated to redefine AI development, pricing, and reliance on domestic AI chip supply chains in China, serving as a potential catalyst for accelerating AI application deployment [1][2]. - The R2 model is expected to achieve significant advancements in multilingual reasoning and code generation, offering a hybrid model with lower power consumption and smaller parameter scale, while being cost-effective compared to its predecessor R1 [2][9]. - The model's efficiency is projected to lower computational requirements, facilitating AI commercialization and expanding total demand, potentially disrupting the AI market [2][10]. Summary by Sections R2 Model Overview - R2 represents the second major iteration of DeepSeek's reasoning model, promising improvements in multilingual reasoning and code generation, with a focus on efficiency and cost reduction [2][9]. - The model is designed to be multimodal, featuring enhanced visual capabilities and a significant reduction in operational costs compared to R1 [2][13]. Supply Chain Developments - The R2 model is supported by a robust ecosystem of Chinese companies, leveraging Huawei's Ascend 910B chip cluster for training, which signifies a shift towards a localized supply chain [3][17]. - DeepSeek aims to reduce dependency on external chip manufacturers, contrasting with the previous reliance on NVIDIA GPUs for training the R1 model [17][20]. Market Impact - The report suggests that DeepSeek's advancements will benefit local GPU, GDDR, and China's HBM sectors, indicating a positive outlook for these industries amidst a broader AI market recovery [20][22]. - The performance of DeepSeek's models, particularly in the context of increasing computational demands during inference, is expected to drive further innovation and resource allocation within the AI ecosystem [20][23]. Competitive Landscape - DeepSeek's approach emphasizes software-driven resource optimization rather than hardware dependency, which could lead to significant cost reductions and efficient training of large models [23][24]. - The report highlights the competitive pressure on NVIDIA from Huawei's Ascend chips, which are designed to match NVIDIA's performance while being domestically produced [17][20].

Core Insights - The next "battlefield" for artificial intelligence (AI) is in terminal applications, with a significant trend towards AI integration in devices like smartphones, smart glasses, and smart home systems by 2025 [1][2] - Shenzhen is positioned as a global leader in electronic information and hardware manufacturing, providing a solid foundation for AI terminal product production [1][3] - The Bao'an district in Shenzhen is actively pursuing the "AI + terminal" strategy to capture the high ground in the AI terminal industry, aiming for substantial growth in AI technology applications [1][4] Industry Growth and Projections - The AI terminal industry is expected to experience a "tsunami-like" growth, with IDC predicting a 20% increase in shipments of AI smartphones, tablets, and computers in China by 2025, and a staggering 99% increase in smart glasses and wearable devices [3] - Shenzhen's action plan aims for the AI terminal industry to reach over 800 billion yuan by 2026, with a target of 1 trillion yuan and the production of over 150 million AI terminal products [3] Bao'an District's Industrial Strength - Bao'an's smart terminal industry cluster is projected to achieve an added value of 24.36 billion yuan in 2024, reflecting an 8.4% year-on-year growth, with 601 enterprises in the cluster [4] - The district is home to notable companies like YingShi Innovation and Zhaowei Machinery, covering various AI terminal fields [4][5] Supply Chain and Innovation - Shenzhen's supply chain advantages, particularly in PCB (printed circuit board) manufacturing, are crucial for the hardware innovation needed for AI terminals [5] - Leading PCB manufacturers in Bao'an are benefiting from the AI terminal innovation cycle, with Pengding Holdings expected to achieve a revenue of 35.14 billion yuan in 2024, a 9.59% increase [5][6] Capital Market Engagement - Two Bao'an companies, YingShi Innovation and SwitchBot, have recently gained attention in the capital market, showcasing the integration of AI technology in their products [6][7] Ecosystem Development - The Greater Bay Area's AI companies excel in their ability to implement AI in real-world scenarios, supported by a robust manufacturing base in Bao'an [8] - Bao'an's industrial ecosystem is characterized by a diverse range of manufacturing enterprises, with over 5,601 large-scale industrial companies, accounting for nearly 40% of Shenzhen's total [8][9] Policy and Market Synergy - Bao'an is focusing on enhancing its industrial chain and supporting AI transformation in key sectors, including e-commerce and logistics, to strengthen its competitive edge [9] - The district is implementing action plans to foster the development of the smart terminal industry, including establishing public service platforms and creating demonstration projects in smart home and health sectors [9]

Group 1 - Baidu's AIDU program aims to recruit top talent for AI technology leadership, with no salary cap for offers to 2026 graduates [1] - The AIDU program has expanded recruitment by over 60% compared to last year, covering 23 core business areas and 11 research directions [1] - Baidu has invested 180 billion yuan in AI research and development, with a significant portion allocated to talent cultivation [2] Group 2 - Baidu plans to train 10 million AI talents over the next five years, building on its previous goal of training 5 million by 2024 [2] - Other major tech companies, such as Alibaba, are also ramping up recruitment efforts, with nearly 50% of their 3,000 open positions related to AI [2] - High salaries are being offered in the AI field, with top positions in large model companies reaching monthly salaries of 60,000 yuan [3]

Core Insights - Baidu's "AIDU Plan" for 2026 aims to recruit top-tier talent with no salary cap, focusing on candidates passionate about AI technology [1][2] - The program offers personalized training paths and one-on-one mentorship from technical experts to help participants excel in the AI field [1][6] Recruitment Expansion - The recruitment for the 2026 "AIDU Plan" has increased by over 60% compared to last year, covering 23 core business areas and 11 research directions, including large model algorithms and machine learning [6] - This initiative represents Baidu's largest-scale recruitment for top AI talent to date [6] Training and Resources - Participants will engage in core AI projects, access cutting-edge technology challenges, and utilize significant computational resources and user scenarios [6] - Baidu has invested 180 billion yuan in AI research and development, with a key focus on talent cultivation [6] Industry Context - Other major tech companies, such as Alibaba, are also ramping up recruitment efforts, with Alibaba offering over 3,000 positions for the 2026 internship program, nearly half of which are AI-related [6] - Leading AI firms are offering competitive salaries, with positions like deep learning researchers commanding monthly salaries between 80,000 to 110,000 yuan, translating to annual salaries exceeding 1 million yuan [7]

百度近期举办的AIDU计划OpenDay活动，再次让其2026届"AIDU计划"受到关注！ "AIDU计划"是百度推出的一项精英招募计划，以培养AI技术领军人才为目标，特别注重候选人对技术的纯粹热爱与追求。加入该计划的学员有机会接触到最前沿的 研究课题，并在业务场景中实现技术的落地应用。百度将为每位学员量身定制个性化的培养路径，并配备专属技术专家导师进行一对一指导，助力他们快速成长为 AI领域的佼佼者。 今年5月，百度2026届"AIDU计划"正式启动，招募对象为2026届博士和硕士生，倾向于超级学霸、学术大神、竞赛高手和工程大牛。 此次活动传出，为招纳到顶尖的校园人才，百度2026届"AIDU计划"的offer薪资上不封顶。 在此次AIDU计划OpenDay活动中，百度透露，相比去年，2026届"AIDU计划"岗位招聘扩增超60%，覆盖百度23个核心业务和11类研究方向，包含大模型算法、大 模型基础架构、机器学习、语音技术、智能体等，是其最大规模的顶尖AI人才招聘。 "百度会像培养飞行员一样，培养未来的AI领航者。"百度方面称。据了解，在培养体系方面，学员不仅可以参与核心AI项目，接触前沿技术挑战，还能享受 ...

Core Viewpoint - The article emphasizes the importance of innovation for companies to thrive in a competitive landscape, highlighting that waiting and observing can hinder progress and success [2][4]. Group 1: Innovation and Competition - Chinese technology companies have gained global attention through significant innovations, such as DeepSeek and DJI, showcasing the potential of autonomous innovation [2]. - Founders of leading companies express a sense of urgency and the necessity for continuous innovation to maintain competitiveness, indicating that past strategies may not be applicable in the future [3]. - The article warns against complacency, using Nokia as an example of a company that failed to adapt and innovate, leading to its decline in the smartphone era [3]. Group 2: Embracing Failure - The article discusses the need for a culture that tolerates failure in the innovation process, suggesting that many successful innovations are built on lessons learned from previous failures [4][5]. - It highlights the importance of allowing innovators the space to experiment and learn from mistakes, as exemplified by Huawei's approach to innovation [5]. Group 3: Managing Expectations - There is a caution against setting unrealistic expectations for innovation outcomes, as some innovators may face setbacks when high expectations are not met [6]. - The article stresses that innovation is a gradual process that requires patience and realistic goal-setting, advocating for a balanced approach to innovation that respects the time needed for development [6]. Group 4: Technological Advancements - Recent technological breakthroughs in China, such as advancements in robotics and aerospace, demonstrate the long-term commitment and perseverance of research teams [6]. - The transformation of Beijing's Zhongguancun from a market to a tech hub illustrates the importance of sustained institutional support for innovation [6].

Core Viewpoint - The article discusses the transition from Global AI to Local AI, emphasizing the need for countries and companies to establish their own data stacks to overcome the "three mountains" of power held by the U.S. in AI technology, models, and data [3][10]. Group 1: Transition to AI - The shift from traditional internet to AI represents a fundamental change in user habits, traffic sources, and business foundations [2]. - ChatGPT has rapidly gained 800 million users, showcasing the speed of AI adoption, while other AI companies are experiencing significant revenue growth [7]. - The emergence of DeepSeek signifies a move towards global equity in AI, challenging the dominance of U.S.-based AI solutions [7][10]. Group 2: The Three Mountains - The "three mountains" that need to be overcome include: 1. **Computing Power Dominance**: The U.S. maintains control through CUDA, necessitating the development of alternative systems like Huawei's CANN and AMD's ROCm [8]. 2. **Model Dominance**: The closed nature of U.S. models limits access, prompting the need for open-source alternatives like DeepSeek [9]. 3. **Data Dominance**: The reliance on English-dominated datasets restricts the development of localized AI solutions, highlighting the need for diverse, multilingual datasets [9]. Group 3: The Future of Programming - The article predicts the decline of "code illiteracy," with more individuals becoming capable of programming as AI tools simplify the coding process [11][12]. - The number of developers is expected to grow significantly, with GitHub reporting 190 million developers, increasing by 20% annually [11]. - The role of traditional programmers will evolve, as many tasks can now be automated by AI, allowing non-programmers to create applications independently [12][15]. Group 4: AI's Impact on Hardware - AI is transforming not only software but also hardware, enabling low-cost programming of physical devices [16]. - The integration of AI with hardware manufacturing in China presents significant opportunities, as demonstrated by successful startups leveraging AI for product development [17]. - The future will see a blend of software and hardware capabilities, allowing for innovative applications in various industries [17]. Group 5: The Future Landscape - The next decade is expected to witness a massive industrial transformation driven by AI, with every individual gaining access to powerful AI tools [18]. - The shift from digitalization to intelligent systems will redefine the boundaries of software development and user interaction [18].