Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The rapid development of large model technology is fundamentally transforming the global computing paradigm, with a shift from traditional CPU cloud computing to GPU-centric intelligent computing [3] - The cloud service industry's value chain is being reshaped, with profound changes in the business logic, commercial models, and competitive factors across IaaS, PaaS, and SaaS layers [3] - The industry is transitioning from a "compute-first" approach to building model ecosystems and commercializing applications, with a significant application explosion expected around 2025 [16][19] Summary by Sections Industry Overview - The intelligent computing industry has formed a four-layer structure: hardware, cloud, model, and application, currently transitioning from "compute-first" to "model ecosystem building" and "application commercialization" [10][16] - The industry value transfer trend indicates a shift from heavy investment in infrastructure to a focus on model ecosystem construction and the commercialization of industry-specific agents [19] IaaS Layer Opportunities - The core value of the IaaS layer lies in selling GPU computing power, with high-end card retention and vertical industry capability construction being key to capturing high-value clients [30][33] - Major clients include internet giants, government enterprises, and AI-driven emerging industries, all of which have significant demand for GPU computing power [31] - The growth path for IaaS involves selling bundled solutions of IaaS, PaaS, and MaaS to industry clients, enhancing customer stickiness and increasing average transaction value [36] PaaS Layer Opportunities - MaaS is becoming the core revenue entry point for cloud vendors, with those possessing self-research capabilities needing to adopt a dual strategy of open and closed source to lock in customers [41][42] - The success of MaaS hinges on the ability to provide a rich model marketplace and a comprehensive toolchain for clients, driving resource consumption in IaaS and PaaS layers [42][44] SaaS Layer Opportunities - The SaaS market is shifting towards deep vertical integration, where the ability to build industry-specific products is crucial for customer retention [52][55] - Large cloud vendors face challenges from smaller firms that leverage low prices and localized services to capture market segments that larger companies cannot reach [55] - Effective strategies for entering the SaaS market include "soft-hard integration" and building Agent platforms to transform from direct competitors to value integrators and ecosystem enablers [57][59]

Group 1 - The company, Junxin Co., is focusing on the integration of waste incineration with emerging fields such as digital industry and intelligent manufacturing [2] - A strategic cooperation agreement has been signed with Changsha Digital Group Co., aimed at developing "waste-free cities," environmental digital upgrades, green electricity, and collaborative development in the intelligent computing industry [2] - The company will disclose any significant developments related to this cooperation in accordance with regulations [2]

根据协议，三方将聚焦智算产业核心环节，整合资源优势形成发展合力：扬州大数据集团将依托数据技术与资源 优势，构建智算中心的数据底座与安全屏障；扬州广陵新城投资发展集团将发挥产业载体运营与生态培育优势， 为智算中心提供落地支撑与场景对接，推动智算能力与制造、文旅等本地特色场景快速适配。 其中，作为领先的AI基础设施及智算云提供商，九章云极DataCanvas将充分发挥在普惠算力领域的技术优势，通 过创新研发的九章智算云平台及"按需配置、即时响应"的弹性供给机制，解决传统AI算力成本高企、利用率低、 供需错配等痛点。锚定扬州市特色产业核心需求，九章云极将为普惠智算中心建设提供全维度支撑——覆盖从底 层算力调度到上层大模型微调应用的全栈AI解决方案，同步输出稳定可靠的普惠算力服务能力，为当地"AI+"场 景的深度应用落地筑牢根基。 此次三方合作不仅是政企协同共筑智算生态的典范，更标志着扬州在构建"算力+算法+数据"新型基础设施方面迈 出关键一步。随着普惠算力服务的广泛渗透，将有力支撑扬州市特色产业体系的数字化转型，为长三角数字经济 一体化发展注入新动能，助力打造全国智算赋能产业升级的标杆样板。 近日，由扬州市国资委、 ...

OISA(全向智感互联架构)协议标准旨在打造一个高效、智能、灵活、开放的AI芯片互联体系，并具备 全方位连接、智能化感知的下一代先进互联能力。通过实现高效互联，该体系可支撑超节点智算集群性 能的纵向扩展。相较于OISA 1.1版本，OISA 2.0进一步将支持的AI芯片数量提升至1024张，带宽突破 TB/s级别，AI芯片互联时延缩短至数百纳秒，为大模型训练、推理及高性能计算等数据密集型AI应用 提供有力支撑。 作为中国移动投资的国产GPU创新企业及生态合作伙伴，摩尔线程深度参与OISA标准的制定，积极贡 献其在AI与计算领域的核心技术能力，推动构建开放、协同的国产软硬件生态。目前，公司旗舰级AI 训推产品已全面支持OISA 1.1标准，展现出在兼容性、协同性和性能方面的显著优势，实现对主流AI框 架、模型及应用的广泛适配与高效支撑。 在OISA 2.0实施的关键阶段，摩尔线程继续与业界伙伴紧密协作，共同推进该标准的演进与落地。在后 续产品迭代中，摩尔线程将持续集成OISA最新技术要求，不断提升产品先进性和优化架构，助力我国 GPU基础软硬件生态实现更高水平的自主创新与融合发展。 近日，在2025中国算力大会 ...

《贵阳市算力产业促进条例》首次以地方性法规形式明确"算力产业"内涵，其涵盖"算力基础设施建 设、软硬件研发制造、技术创新、服务应用及安全保障"等全链条体系。《贵阳市算力产业促进条例》 共五章三十二条，其中明确：县级以上人民政府及其有关部门应当采取措施促进算力产业和相关配套产 业协同发展，建立完善算力产业链。同时，对"开展协同立法，强化区域一体化发展""锚定'智算优先'， 打造全国智算产业新高地""强化跨区域算力协作，释放资源配置新动能""调动经营主体积极性，激发算 力市场新活力"等方面，《贵阳市算力产业促进条例》也作出了相应的规定。 算力产业是数字经济发展不可或缺的基础支撑和核心引擎。近年来，作为全国首个国家大数据综合试验 区的核心区，贵阳市、贵安新区立足自身优势，加快推进算力产业发展。目前，贵安新区已成为全国国 产化智算资源最多、能力最强的地区之一。 贵州省贵阳市率先在全国开展算力方面的地方立法，为算力产业依法有序发展提供法治保障。记者近日 从《贵阳市算力产业促进条例》新闻发布会上获悉，《贵阳市算力产业促进条例》于8月1日起施行，此 举为国家和省级层面开展相关立法工作提供可借鉴的实践经验。 （文章来源：科技 ...

Core Viewpoint - The international academic seminar on high-level multilingual models highlighted the urgent need to address the digital divide affecting low-resource languages, as global mainstream models inadequately support these languages, posing a risk of marginalization for small language countries [1][5]. Group 1: Expert Opinions - Professor Vlado Delić from Serbia emphasized that Serbian language representation in general models is less than 0.1% in token usage, significantly lower than Slovenian, advocating for national-level models that reflect cultural identity to avoid translation errors in critical fields like healthcare and law [3]. - Avner Algom, founder of the Israeli Human Language Technology Association, stated that language services should not be designed solely for major languages, advocating for technological equity for small languages [5]. - Nipat Jongsawat from Thailand highlighted that language sovereignty is a strategic necessity for nations, not merely a choice [5]. Group 2: Technological Developments - Liu Cong, director of iFlytek Research Institute, reported that their multilingual model, Spark X1, expanded from supporting 81 languages in October 2022 to over 130 languages by July 2023, aiming to provide a comprehensive multilingual model and applications [5]. - The Spark X1 model reportedly outperforms GPT-4.1 in key languages such as Arabic, German, French, Korean, and Japanese, while the speech synthesis model supports 55 languages with leading industry performance [5]. - Zhang Xiao, deputy general manager of iFlytek's intelligent computing division, identified challenges in the rapid iteration of computing power and low efficiency in existing resources, proposing a five-element solution combining computing power, algorithms, data, applications, and ecosystem [7]. Group 3: Data Quality and Collaboration - Gábor Prószéky, director of the Hungarian Linguistics Research Center, stressed that data quality is more critical than quantity for building reliable large language models, noting the unique challenges posed by the Hungarian language's complex morphology [7]. - His team has developed the PULI model family, collaborating with Chinese AI counterparts to create a complete closed loop from training to application [7].

Group 1: Core Insights - The event held by DataCanvas in Shanghai showcased the company's latest achievements in AI computing power accessibility, providing practical solutions for the high-quality development of the AI industry [1][2] - Shanghai is actively implementing the national "East Data West Computing" strategy, introducing new industrial policies to support the development of the intelligent computing industry, aiming for a transformation towards self-controllable and green efficiency by 2025 [3][4] - DataCanvas has launched its new product "New Start" at the event, which focuses on commercializing intelligent agent technology and aims to create a comprehensive solution for enterprise-level intelligent agents [4][5] Group 2: Technological Innovations - DataCanvas's Alaya NeW Cloud has successfully overcome performance bottlenecks, achieving "second-level generation of millions of tokens," aimed at providing intelligent computing infrastructure services for global AI innovation enterprises [4][6] - The company has introduced a unique "1-degree computing power" measurement standard to standardize the supply and elastic scheduling of computing resources [4][6] Group 3: Market Strategy and Applications - DataCanvas has tailored computing power and channel policies for the Shanghai market, establishing a service system that supports flexible scheduling from single cards to clusters, addressing the differentiated computing power needs of key sectors like finance and healthcare [6][7] - The collaboration with various industries has demonstrated significant results, such as the partnership with Wuxi Yinlv Shandong AI Technology Co., which has transformed music creation through AI technology, producing millions of works with minimal sample learning [7][8] Group 4: Industry Impact - The establishment and development of DataCanvas in Shanghai not only accelerates the local intelligent computing industry but also provides valuable experience for the national intelligent computing industry construction [7] - The distributed computing network built by Alaya NeW Cloud aims to optimize computing resources across regions, making AI computing power a widely accessible social resource, thus supporting the high-quality development of China's digital economy [7][8]

Core Viewpoint - The 2025 DEMO WORLD Enterprise Innovation and Investment Conference will be held in Shanghai Songjiang, focusing on the integration of technological and industrial innovation, particularly in the intelligent computing service sector [1] Group 1: Event Overview - The conference will feature a special session on "Intelligent Computing Services & Shanghai Songjiang Economic Development Zone," aimed at showcasing the vitality of the intelligent computing industry and fostering cross-industry collaboration [1] - The event is organized by Chuangyebang, in collaboration with various local government entities, to promote innovation and investment opportunities in the region [1] Group 2: Industry Development - The intelligent computing service sector is one of the seven key industries in Songjiang's "2+7" modernization industrial system, with plans to establish a core supply source for intelligent computing in the Yangtze River Delta by around 2030 [1] - Songjiang aims to support the intelligent computing industry through nine initiatives, including financial support of up to 200 million yuan for qualifying enterprises [1] Group 3: Economic Performance - Songjiang Economic Development Zone ranks 16th among 233 national-level development zones in China and 2nd in Shanghai, housing 108 high-tech enterprises and 47 specialized and innovative companies [2] - The intelligent computing capacity in the Songjiang Economic Development Zone reaches 31,300 PetaFLOPS, positioning it among the leaders in the Yangtze River Delta [2] Group 4: Conference Activities - The conference will include presentations on the latest industry policies and investment environments, as well as deep sharing from leading enterprises and their partners [3] - A "New Quality Discussion" segment will feature over 10 intelligent computing service companies sharing their latest technologies and products, followed by a roundtable discussion on investment trends [4]

Core Insights - The emergence of DeepSeek has significantly elevated the intelligent computing industry, demonstrating the "Jevons Paradox" where technological advancements lead to increased demand despite reduced resource consumption [1] - The cost of model training has decreased by 85% over the past three years, while the elasticity of computing power demand has expanded sixfold, making AI technology more accessible to all enterprises [1] - By the end of 2024, China's intelligent computing AI computing power supply is expected to reach 1450 EFlops, with a projected growth rate of over 40% annually for the next three years [1] Group 1: Challenges in Intelligent Computing - The first major challenge arises from the exponential growth in computing power demand driven by large models, which requires over 200 times the hardware supply [5] - The second challenge is the rapid penetration of AI across various industries, leading to difficulties in integrating AI technology with specific scenarios, as many emerging applications lack best practices [6] - The third challenge pertains to the ecosystem, where developers face fragmentation of tools, high learning costs, and uneven resource access, complicating collaboration between traditional enterprises and AI technology suppliers [7] Group 2: Strategic Innovations and Solutions - Huawei emphasizes the need for a comprehensive transformation involving innovations in computing architecture, resource scheduling, business models, and computing infrastructure to address the supply-demand contradiction [3] - Huawei is committed to a long-term strategy that supports the intelligent computing industry through foundational infrastructure, AI ecosystem development, and product empowerment [15][16] - The company has established a complete solution for the MoE architecture, enhancing resource utilization by 20% through dynamic balancing of multiple experts [11] Group 3: Ecosystem Development and Collaboration - Huawei's strategy includes hardware openness, software openness, enabling partners, and talent development, aiming to create a collaborative AI industry ecosystem [12][14] - The company has partnered with over 2,500 industry collaborators and developed more than 5,800 certified solutions, demonstrating its commitment to ecosystem building [14] - Huawei's focus on synergizing computing and networking technologies positions it uniquely to address the challenges of intelligent computing and enhance overall performance [20]