Core Insights - The article discusses the ongoing series of closed-door social events called "Jinqiu Xiaofanzhuo," organized by Jinqiu Capital, focusing on AI entrepreneurs and technology discussions [3][4][11] - Recent discussions have centered around multi-modal technology, AI computing architecture, embodied intelligence, and AI hardware innovation, highlighting the practical challenges and opportunities in these areas [1][12][18] Group 1: Event Overview - "Jinqiu Xiaofanzhuo" is a weekly event held in cities like Beijing, Shenzhen, Shanghai, and Hangzhou, aimed at fostering genuine conversations among top entrepreneurs and tech experts without the usual corporate presentations [3][4] - The series has successfully hosted 25 events since its inception in late February, with summaries available for earlier sessions [3][11] Group 2: Recent Discussions - The latest discussions included topics such as the future of embodied intelligence, focusing on five key perspectives: ontology, cognition, interaction, data, and computing power [14][12] - The challenges of data and model architecture decisions were emphasized, particularly the need for high-quality data and the exploration of generative world models [16][35] Group 3: AI Hardware Insights - The event on AI hardware featured discussions on differentiation strategies, with a focus on product details and user experience [23][24] - Key technical variables for AI hardware entrepreneurs include edge computing power and memory solutions, which are crucial for enhancing user experience and privacy [24][25][26] Group 4: AI Computing Architecture - The demand for AI computing power is expected to grow significantly, driven by the need for concurrent AI agents in daily life, leading to potentially unlimited power consumption [35][36] - The article highlights the current shortage of high-end AI computing resources and the competitive landscape among leading companies [36][37] Group 5: Future Directions - The future of AI models is anticipated to move beyond reliance on human data, with a focus on self-exploration and overcoming human knowledge limitations [38][39] - The next generation of AI computing architecture is expected to integrate advanced technologies like liquid cooling and memory processing units, addressing challenges in reliability and efficiency [41][43]

Investment Rating - The report does not explicitly provide an investment rating for the industry or specific companies involved in the RISC-V architecture and NVIDIA's CUDA support. Core Insights - NVIDIA's announcement at the 2025 RISC-V China Summit signifies a strategic shift in the global AI computing landscape, evolving from a duopoly of x86 and ARM to a tripartite balance with RISC-V [1][2][27] - The integration of CUDA with RISC-V allows RISC-V processors to function as the main CPU in AI systems, marking a significant entry into the mainstream AI computing domain [1][26] - The move enables RISC-V to leverage NVIDIA's extensive software ecosystem, facilitating rapid development and innovation in AI applications [2][28] Summary by Sections Event Overview - At the RISC-V Summit China 2025, NVIDIA announced that its CUDA platform will support RISC-V architecture, allowing RISC-V processors to act as core application processors in AI systems [1][26] Strategic Implications - This development indicates a major transformation in the computing power structure, traditionally dominated by x86 and ARM, now including RISC-V as a key player [2][27] - NVIDIA's support for RISC-V is seen as a strategic move to decouple its GPU offerings from any single CPU architecture, ensuring its central role in a diversified computing future [4][31] Ecosystem Development - The report emphasizes that the greatest challenge for new computing architectures is building a robust software ecosystem, which NVIDIA's support for RISC-V aims to address by enabling access to its established CUDA ecosystem [3][28] - RISC-V's modular design allows for customized processors tailored to specific AI tasks, enhancing efficiency and cost-effectiveness compared to traditional CPUs [6][30] Geopolitical Context - The open and neutral nature of RISC-V is particularly relevant in the context of global technological competition, providing countries like China with a path to technological sovereignty [4][30] - NVIDIA's strategic intent is to facilitate local developers' access to mainstream AI software ecosystems while promoting the development of sovereign RISC-V chips [4][30]