Summary of the Conference Call for Zhengyuan Wisdom Company Overview - **Company**: Zhengyuan Wisdom - **Industry**: AI Large Model Applications in Education Key Points and Arguments AI Large Model Development - Zhengyuan Wisdom initiated AI large model applications after the release of ChatGPT 3.5 in June 2023, with a focus on higher education institutions [3] - The company provided AI large model applications for Lanzhou University, which will officially launch on March 15, 2024, marking it as the first application in a domestic 985 university [3] - The actual user count for Lanzhou University and Northwest Normal University exceeds 40,000 and 30,000 respectively [3] Data Security and Privacy Concerns - High education institutions have stringent data security and privacy requirements, preferring localized deployments over public cloud solutions [4][5] - Over 98% of the educational institutions contacted are unwilling to adopt public cloud models, emphasizing the need for localized deployment of AI large models [5] Computational Resources in Higher Education - Universities face a shortage of computational resources, with existing resources primarily allocated to specialized teams, leaving little for digital campus initiatives [6] - Zhengyuan Wisdom optimized its technology to run AI large models on mid-range computational power, keeping costs under 1 million RMB, which is lower than HRS integrated machine costs [4][6] Collaboration with Huawei - Zhengyuan Wisdom has established a deep collaboration with Huawei, launching a smart campus solution that received awards and technical certification [4][8] - The partnership includes joint seminars and the release of the Zhengyuan Wisdom Campus Service Large Model, which is recommended by Huawei's enterprise solutions club [8] AI Integrated Machine Development - The company plans to enhance existing products with AI large models and collaborate with Huawei to develop AI integrated machines for localized deployment [10] - AI integrated machines are categorized into basic computational types and those including industry applications, with costs ranging from 1.3 million to 1.5 million RMB for NVIDIA H20 series nodes [12] Market Demand and Budgeting - The education sector has a rigid demand for AI applications, with a total budget of approximately 350 million RMB for applications across multiple universities [4][21] - The average budget for AI applications in universities is around 10 million RMB, indicating a vast market potential with over 3,000 universities in China [22][23] Application Scenarios and Efficiency - AI large models are expected to enhance various educational functions, including teaching assistance, administrative management, and logistics services [14][25] - The implementation of AI can lead to significant cost reductions and efficiency improvements, as evidenced by successful case studies in universities [25] Challenges in Information Technology Construction - The current phase of information technology construction in universities faces siloed applications, making it difficult for users to find specific functionalities [26] - Recommendations include integrating applications into a single platform to improve efficiency and user experience [26] Future Directions and Strategic Goals - Zhengyuan Wisdom aims to transition from a single application model to a platform-based, integrated, and digital transformation approach [30] - The company aspires to become a leading brand in digital logistics and campus digital services within the education sector [30] Additional Important Insights - The company is focusing on practical delivery capabilities and maintaining transparent communication with clients to ensure project success [20] - The impact of tightened bank investments in educational information technology in 2024 has led to a shift towards self-funded projects by universities [28][29]

Investment Rating - The report does not explicitly state an investment rating for the semiconductor industry Core Insights - AI computing chips are considered the "engine of the AI era," with significant growth in global computing demand driven by the ChatGPT trend and the acceleration of AI model iterations [6][12] - The global computing scale is expected to grow from 1,397 EFLOPS in 2023 to 16 ZFLOPS by 2030, with a compound annual growth rate (CAGR) of 50% from 2023 to 2030 [6][25] - The AI server market is projected to reach $125.1 billion in 2024 and $158.7 billion in 2025, with a CAGR of 15.5% from 2024 to 2028 [29] Summary by Sections 1. AI Computing Chips as the "Engine of the AI Era" - The ChatGPT trend has led to a rapid iteration of AI models by major tech companies, significantly increasing global computing demand [12][19] - AI servers are the core infrastructure supporting generative AI applications, with a growing need for high-performance computing resources [28][29] 2. Dominance of GPU and Growth of Custom ASIC Market - AI computing chips are primarily based on GPUs, with a significant market share held by NVIDIA, which dominates the global AI chip market [42][45] - The custom ASIC chip market is expected to grow rapidly, driven by cloud vendors seeking to diversify supply chains and enhance bargaining power [6][7] 3. DeepSeek's Role in Accelerating Domestic AI Computing Chip Development - DeepSeek's technological innovations are expected to enhance the efficiency of domestic AI computing chips, facilitating their rapid development and market share growth [6][7] 4. Henan Province's Focus on AI Computing Chips - Henan Province is actively developing its AI computing chip industry, establishing a foundational ecosystem and attracting key enterprises [9][10]

Investment Rating - The report indicates a positive investment outlook for the integrated machine and AI SoC sectors, particularly in the context of AI model deployment and local data security needs [3][11]. Core Insights - The demand for integrated machines has surged following the release of the Deep Seek AI model, with significant interest from government and enterprise sectors due to their data security requirements [3]. - The integrated machine is designed for AI model applications, effectively shortening deployment cycles and lowering barriers to entry, with a projected demand of 70,000 units in the government and enterprise sectors by 2025, translating to a market size of 54 billion yuan [3][11]. - The Deep Seek distilled small parameter models demonstrate excellent performance on terminal devices, achieving real-time question answering with a 1.5B model and suitable for text summarization and image description with 7B/8B models, requiring a minimum of 4-5GB of memory under INT4 quantization [3][5]. - Domestic computing power is expected to play a crucial role in the integrated machine sector, aligning well with mainstream downstream demands, although challenges in software-hardware collaboration remain [3][7]. - Quantization techniques are highlighted as a means to reduce AI hardware costs by converting model parameters from 16-bit floating-point to 8-bit integers, thus decreasing model size and computational complexity [3][8][9]. - The report notes a significant reduction in AI inference costs, which is driving the trend towards edge computing, with lightweight AI hardware gaining advantages in both edge and cloud environments [3][15]. - In the smart automotive sector, companies are integrating AI technologies to enhance smart cockpit functionalities, with BYD leading the way in adopting new AI chips in its vehicles [3][17]. - The domestic automotive chip sector is making strides, with companies like Yikatong collaborating with Volkswagen to export new SOC chips, indicating a growing acceptance of domestic chips in international markets [3][20]. Summary by Sections Integrated Machines - Integrated machines are tailored for AI model applications, providing a plug-and-play computing solution that meets high data security requirements for sectors like government and finance [4][10]. - The projected demand for integrated machines in the Chinese server market is expected to reach approximately 70,000 units by 2025, with a market potential of 54 billion yuan [11]. AI Model Performance - The Deep Seek distilled models are effective in reducing hardware resource requirements while maintaining performance, making them suitable for various applications [5][16]. Domestic Computing Power - The report emphasizes the importance of domestic computing power in the integrated machine sector, with a need to overcome challenges related to precision support in AI chips [7]. Cost Reduction Techniques - Techniques such as fixed-point quantization are crucial for lowering AI hardware costs and improving overall efficiency [8][9]. Smart Automotive Sector - The integration of AI in smart vehicles is on the rise, with significant advancements in automotive chip technology and collaborations with international partners [17][20].