算力平台V2.0

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科华数据发布算力平台V2.0:构建“1+4+X”算力服务体系
Huan Qiu Wang· 2025-07-30 04:08
Core Insights - The forum highlighted the importance of diverse computing power infrastructure in driving the large-scale implementation of artificial intelligence [1][6] - Shanghai is actively implementing national strategic deployments to accelerate the development of new-generation information infrastructure, aiming to become a globally influential "International Digital Capital" [1] - Keda Data emphasizes its core competencies in power electronics and data center experience to provide comprehensive solutions from planning to intelligent operation [1][3] Group 1: Key Developments - Keda Data's Senior Vice President presented five characteristics and challenges of computing power deployment in the AI era, along with three core capabilities of their infrastructure [3] - The newly launched Computing Power Platform V2.0 integrates diverse computing resources across four major intelligent computing clusters, enabling various industry applications [5] - The forum included multiple strategic partnership signings with companies across AI chips, software algorithms, cloud computing, and research institutions, reinforcing Keda Data's technical strength and service capabilities [5][6] Group 2: Future Directions - Keda Data aims to deepen collaboration with industry partners to accelerate the construction of efficient, green, and open computing power infrastructure [6] - The forum showcased innovative achievements in modular intelligent computing rooms and liquid cooling systems, emphasizing the critical role of reliable computing power infrastructure in AI development [6]
算力筑基 模型进阶 AI应用实干突围
Zhong Guo Zheng Quan Bao· 2025-07-28 21:05
Group 1: AI Industry Development - The 2025 World Artificial Intelligence Conference (WAIC) showcased significant advancements in AI applications, marking the transition into a "practical era" of AI technology [1][6] - The demand for computing power is expected to increase dramatically, with predictions of a hundredfold to thousandfold growth in training computing power requirements due to the rapid evolution of AI applications [1][4] - AI foundational models are shifting their core competitiveness from "data + scale" to "self-optimization + multi-modal native integration," facilitating the transition of large models from laboratories to industry [4][5] Group 2: Computing Power Infrastructure - Companies like Huawei and ZTE presented innovative supernode solutions, with Huawei unveiling the Ascend 384 supernode, which enhances resource utilization by allowing 384 cards to work collaboratively as a single computer [2][3] - The introduction of the LightSphere X supernode by Shanghai Yidian and partners utilizes optical interconnect technology to overcome traditional physical limitations, allowing for elastic scaling and reduced deployment costs [2][3] - Companies are adapting to AI demands by developing hardware products, customized data center solutions, and intelligent scheduling platforms for heterogeneous computing [3][4] Group 3: AI Applications and Use Cases - AI agents are becoming pivotal in various sectors, evolving from tools to "digital employees" capable of analysis, execution, and optimization in government, finance, industry, and healthcare [5][6] - The Rokid Glasses, an AI + AR smart eyewear, exemplifies the integration of AI technology into consumer products, enabling users to perform tasks like information retrieval and translation through voice commands [6][7] - The Galbot robot, showcased in a simulated supermarket environment, demonstrates advanced capabilities in product recognition and retrieval, with applications already implemented in retail and industrial settings [7][8]