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“ACT”三步走,破题行业智能化的华为答案
Guan Cha Zhe Wang· 2025-09-26 10:09
文 观察者网 吕栋 但在技术热潮中,企业发现,真正让AI在业务中扎根、生长并结果,远比想象中艰难。归根结底,AI深入核心生产场景,须直面三大关键问 题:商业价值如何体现?专业数据的竞争力如何构建?应用规模化落地如何实现? 实践出真知。华为通过与银行、电力、医疗等行业伙伴的共同探索发现,行业智能化并非单一技术突破,而是一个包含场景、数据、智能体、 人机协作与治理的系统工程。结合更广泛的实践,华为归纳出了能够帮助行业智能化进一步推进的"五大关键发现"。 第一,场景选择至关重要。 AI的价值更在于与核心生产场景深度融合,从而重塑流程,推动智能产品与服务的交付方式。 第二,垂域数据的 质量,决定行业模型的能力。 行业智能化的落地,仅依赖开箱即用的通用模型是不够的。企业必须基于自身及所在行业积累的大量高质量数 据,对通用模型进行训练和调优,才能形成专属的行业模型,构筑差异化竞争力。 第三,智能体(AI Agents)正在快速规模化,驱动对大规 模推理的旺盛需求。第四,人机协作正在成为新的组织范式。第五,系统化治理与风险管理是必须守护的底线,必须建立有效的治理机制,确 保AI的应用安全、可持续、可信赖。 人工智能的浪潮奔 ...
华为提出行业智能化「三步走」路径,为产业AI落地破题
3 6 Ke· 2025-09-20 13:50
产业 AI 如何落地?华为"三步走"路径为企业解题。 在智能化浪潮席卷全球的时代,没有一家企业不在拥抱AI,但真正能够将其转化为核心竞争力的仍然 凤毛麟角。当众多厂商仍在比拼模型参数之多、算法之新时,更亟待解决的问题是,如何让AI在真实 的业务场景中跑起来,并创造出真金白银的商业价值。 这也是华为试图解答的核心命题。9月19日,在华为全联接大会2025期间,华为公司高级副总裁、企业 销售总裁陈雷分享了华为在智能化转型过程中的实践与思考——当AI成为业务创新的核心驱动力,企 业应该如何找到最适合自己的智能化升级路径。 于是,华为将自身的实践经验输出,联合伙伴发布了涵盖政务、教育、医疗、金融、制造等在内的9大 行业解决方案。 华为的实践,正在成为一套可复制、可落地的行业标准范式,帮助千行万业找到最适合自己的转型路 径。 智能化转型的五个关键发现 知名市场调查机构Gartner预测,2027年80%的中国企业,将会部署本地多模型的AGI;到2029年60%的 企业将把AI融入生产系统和产品服务,并成为收入增长主要驱动力。 但有了现成的技术,企业就能拿来用吗?现实是,技术供给和业务价值之间,仍然存在着一道巨大的鸿 沟 ...
华为云肖霏: 找准AI技术锚点,做智能时代更懂政企的云
Sou Hu Cai Jing· 2025-06-21 21:35
Core Viewpoint - Huawei Cloud Stack aims to provide a hybrid cloud solution that better understands the needs of government and enterprise users in the era of intelligence, focusing on AI integration and data utilization [1][3]. Group 1: Huawei Cloud Stack Features - Huawei Cloud Stack will become the first hybrid cloud to adapt to CloudMatrix 384 super nodes, enabling enterprise customers to have their own cloud super nodes locally, enhancing AI computing power for intelligent transitions [3]. - Currently, Huawei Cloud Stack offers over 120 cloud services and more than 50 scenario-based solutions, maintaining the leading market share in the hybrid cloud sector across government, finance, and manufacturing for several consecutive years [3][4]. Group 2: User Segmentation and Solutions - Huawei Cloud Stack recognizes that government and enterprise users are not a monolithic group but can be categorized into four distinct roles: data center engineers, data engineers, AI algorithm model application engineers, and application development engineers [3][4]. - The platform supports users throughout the entire cloud lifecycle, from building to managing cloud resources, enabling efficient resource allocation, data governance, model training, and application development [4]. Group 3: Case Studies - In finance, Huawei Cloud Stack helped a state-owned bank establish a unified computing power platform, allowing data center engineers to deploy 106 DeepSeek R1 instances in just two days, improving efficiency by 70% compared to traditional bare-metal deployments [4][5]. - In manufacturing, Huawei Cloud collaborated with XCMG to create a robust big data platform, enhancing data analysis efficiency and enabling value extraction from operational data of construction machinery [4][5]. - In the steel industry, Xianggang utilized Huawei Cloud Stack to develop a one-stop AI development platform, achieving quality improvement and cost reduction through the deployment of a steel model across over 30 scenarios [5]. - In the energy sector, CNOOC implemented CodeArts to develop a digital platform, reducing development time by 30% and streamlining the deployment of intelligent oilfield management systems from one week to one day [5].