Investment Rating - The report does not explicitly state an investment rating for the industry or specific companies involved Core Insights - The Ascend ecosystem is shifting from a hardware-centric approach to a software-hardware co-design with full open-sourcing, enhancing its ecosystem and industry opportunities [1][8] - The focus in AI acceleration has transitioned from peak chip performance to end-to-end usability, emphasizing the importance of operator libraries and efficient communication-computation overlap [2][9] - The report highlights the need for high-quality documentation and support to build a robust open-source ecosystem that can compete with established frameworks like CUDA [3][11] Summary by Sections Event Highlights - At the AI Chip Summit, Huawei's Ascend chip manager presented a strategic shift towards a fully open-source and integrated software-hardware ecosystem, covering major AI frameworks and tools [1][8] - The collaboration with DeepSeek showcased advancements in operator fusion and system-level performance improvements for complex AI tasks [1][8] Commentary - The "software-first" strategy is essential for competing with CUDA, with a clear roadmap requiring substantial R&D investment and strong engineering governance [2][9] - Data movement is identified as a core bottleneck in AI computing efficiency, necessitating optimizations that can generalize across various model families [10] - A differentiated market strategy aims to lower entry barriers for developers while emphasizing the importance of comprehensive support and examples to enhance user experience [3][11] Industry Perspective - The industry is at a critical development juncture, with increased investment in AI infrastructure and a focus on model innovation [4][12] - Developers are encouraged to conduct proof-of-concept tests to evaluate the efficiency and stability of the Ascend ecosystem [4][12]

Core Viewpoint - The article discusses the ongoing competition between China and the United States in the field of artificial intelligence (AI), highlighting China's strategic use of an "open-source strategy" to potentially disrupt Western AI business models and gain a competitive edge in the future [4][5]. Group 1: US and China's AI Landscape - The US holds a significant advantage in AI technology, particularly in private sector innovation, cutting-edge research, and advanced computing infrastructure, with 40 out of the top 50 AI models globally developed by American institutions [9]. - China excels in the large-scale deployment of AI across various sectors, leading in AI-related publications and patents, particularly in computer vision and natural language processing [4][10]. - China's industrial robot market share increased from 51% in 2023 to 54% in 2024, showcasing its dominance in AI application scenarios [13]. Group 2: Open Source Strategy - China's open-source strategy aims to undermine traditional software profit models by offering high-performance AI models for free, thereby reducing the willingness of users to pay for premium services [21][23]. - The open-source models developed by Chinese companies are rapidly approaching state-of-the-art performance, making them highly competitive against Western counterparts [20][21]. - This strategy not only democratizes access to AI but also positions China to control the hardware ecosystem needed to run these models, as global developers will require robust hardware solutions [23][25]. Group 3: Hardware as a Strategic Resource - The article posits that the AI era has reversed the traditional logic where software was scarce and valuable; now, hardware is becoming the critical resource due to the high demand for advanced AI capabilities [30][34]. - China's manufacturing capabilities and ecosystem allow it to produce hardware that is well-suited for its open-source AI models, creating a strong synergy between software and hardware [25][34]. - The demand for complex hardware, such as robots and AI chips, is expected to rise exponentially, establishing a significant barrier to entry for competitors [33][34]. Group 4: Future Implications - The article suggests that while China faces challenges, such as reliance on high-precision components and potential Western sanctions, it is exploring multiple strategies to enhance its resilience in the AI landscape [36][38]. - The ability to integrate and expand technology across industries will be crucial for long-term economic power, as highlighted by China's current dominance in electric vehicles and industrial robots [39]. - The competition may lead to a fundamental restructuring of the global technology value chain, with China potentially establishing a non-Western AI ecosystem that could redefine global standards and practices [42][43].

Core Viewpoint - Qunhe Technology aims to accelerate global spatial intelligence technology through open-source initiatives, showcasing its latest spatial models, SpatialLM 1.5 and SpatialGen, at its first Tech Day event [3][4]. Group 1: Spatial Models - Qunhe Technology has introduced SpatialLM 1.5, a spatial language model that allows users to generate structured scene scripts and layouts through natural language interactions, addressing limitations of traditional language models in understanding spatial relationships [4][6]. - SpatialGen, a multi-view image generation model, focuses on generating images with temporal and spatial consistency based on text descriptions and 3D layouts, enabling immersive experiences in generated 3D environments [7][8]. Group 2: Open Source Strategy - The company has been implementing an open-source strategy since 2018, gradually releasing its data and algorithm capabilities to foster innovation in spatial intelligence technology [4][10]. - Qunhe Technology's spatial intelligence ecosystem consists of a "space editing tool - spatial synthesis data - spatial large model" framework, which enhances data accumulation and model training through widespread tool application [4]. Group 3: Data and Model Performance - As of June 30, 2025, Qunhe Technology possesses over 441 million 3D models and more than 500 million structured 3D spatial scenes, which significantly contribute to the training and performance of its spatial models [4]. - The previous version, SpatialLM 1.0, quickly gained popularity on the Hugging Face trends list after its open-source release, demonstrating the effectiveness of the open-source model [6]. Group 4: AI Video Generation - The company is developing an AI video generation product that integrates 3D capabilities, aiming to address the challenges of temporal consistency in current AI-generated videos [10]. - Existing AI video creation often suffers from issues like object displacement and spatial logic confusion due to a lack of understanding of 3D structures, which Qunhe Technology seeks to overcome with its new model [10].