英伟达和西门子要打造“工业AI操作系统”，怕是没那么简单

中国信息化周报01-27

▲关注中国信息化周报新视界、新思维、新洞察2026年初，当西门子与英伟达高调宣布深化合作，要共同打造工业AI的“操作系统”时，不少人的第一反应是：工业领域的Windows时刻要来了吗？在中国钢研集团人工智能首席专家张云贵看来，这套路数并不陌生，甚至包藏着一个巨大的雄心。“他们实际上是想复刻当年微软和英特尔合作的情景，”张云贵在接受《中国信息化周报》专访中直指核心，“如果合作成功，这个‘工业AI...

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simple","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"SIEGY":1.95,"SNVD.UK":0.6,"NVDW":0.6,"NVDA":1.96,"NVDU":0.6,"NVDS":0.6,"DIPS":0.6,"NVDQ":0.6,"NVDD":0.6,"NVDY":0.6,"NVIW.SI":0.6,"3NVD.UK":0.6,"NVDG":0.6,"NVDX":0.6,"NVII":0.6,"NVDS.UK":0.6,"2NVD.UK":0.6,"NVD":0.6,"NVD3.UK":0.6,"NVD2.UK":0.6},"content_text":"▲关注中国信息化周报新视界、新思维、新洞察2026年初，当西门子与英伟达高调宣布深化合作，要共同打造工业AI的“操作系统”时，不少人的第一反应是：工业领域的Windows时刻要来了吗？在中国钢研集团人工智能首席专家张云贵看来，这套路数并不陌生，甚至包藏着一个巨大的雄心。“他们实际上是想复刻当年微软和英特尔合作的情景，”张云贵在接受《中国信息化周报》专访中直指核心，“如果合作成功，这个‘工业AI操作系统’的生态一旦成型，圈子的属性会更强，更有排他性。”这其中的玄机，恰恰就在“操作系统”这四个字上。不只是平台，更是一场“概念植入”英伟达和西门子要做的，本质上并非传统意义上的操作系统。张云贵点破了这层窗户纸：“确切来说是一个集成的平台，要统筹AI+工业的各种要素，从硬件到软件到标准接口。”那为何非要用“操作系统”这面大旗？“它之所以要打操作系统的旗号，其实是想形成一种概念植入。”张云贵分析道。这个概念一旦被广泛接受，就会产生连锁反应，从概念的依赖，导致行动的依赖，最终形成产业路径的依赖。西门子的角色至关重要。作为深耕工业领域数十年的巨头，它“知道现在AI进入工业的痛点在哪里”。从研发设计到生产制造、供应链管理，西门子的工业软件覆盖了“研产供销服”的全链条。它的加入，为英伟达的算力和AI框架提供了宝贵的工业场景、专业知识和现成的客户入口。两者的结合，堪称“顶配”：英伟达提供从 GPU、CUDA-X到Omniverse数字孪生和PhysicsNeMo物理AI模型的全栈技术底座；西门子则注入其工业软件框架、自动化技术、高保真工业模型与庞大的行业生态。王牌与算盘：高保真数字孪生与软硬一体那么，他们的突破口在哪？张云贵认为，关键枢纽在于高保真的数字孪生。过去，工业数字孪生多用于离线仿真，受限于算力和技术，难以做到实时、高保真地与生产物理系统同步。而英伟达的Omniverse平台，结合其顶级的算力，恰恰有望扫清这个障碍。“英伟达的那一整套仿真技术，再加上顶级的算力支撑，这个问题有望得到解决。”张云贵说。这种结合可能催生一种新的部署模式。张云贵联想到当年“Wintel联盟”的软硬互促，解释道：“英伟达的硬件会更好地适配工业软件部署的需求，反过来，需求多了又会快速增加硬件的市场空间。”这意味着，未来工业AI的落地中，英伟达会提供深度优化的“工业版”算力方案，从而在更深处绑定客户。中国的优势与真正的战场：物理AI与行业深耕面对这样一个强大的“联盟”，中国的机会在哪里？张云贵指出了另一条路：物理AI与行业Know-how。“在工业领域还是需要物理模型，但这个事情似乎不是西门子和英伟达的强项。”张云贵指出，西门子的基因是通用装备与软件供给，英伟达的基因是底层基础设施。而中国作为世界第一制造业大国，像钢铁这样的重点行业在生产实践中积累了海量的、鲜活的工艺数据和物理规律认知。“只有深耕行业，才能够真正摸清楚这种物理规律。”张云贵认为，这正是我国工业界的“潜在优势”。例如，在钢铁行业，对炼钢、连铸、轧制等过程中复杂的物理化学反应机理和生产工艺的深刻理解，是构建真正可信、可用的工业AI模型的基石。这种源于一线、与生产工艺深度耦合的知识，是任何通用平台短期内难以复制的。当然，将潜在优势转化为商业优势，“中间还有很多障碍”，张云贵坦言，我国需要自己的“枢纽”和“支撑整个工厂运营的AI原生架构”，也需要在算力基础设施和基础支撑软件上形成合力。目前，中国钢研集团与南钢、兴澄特钢联合成立了钢铁人工智能应用基地公司，并准备邀请更多的生态伙伴加盟，就是希望集结各方力量，攻克行业大模型、核心场景验证等共性难题。而西门子和英伟达的合作给了我们一个强烈的启发，那就是有必要跨出钢铁行业进行更广泛的合作，从而构建起“AI+钢铁”的软硬件全栈解决方案。英伟达与西门子的联手，无疑为工业AI的落地投下了一颗重磅炸弹，它试图定义新的游戏规则。然而，工业的复杂性远非消费互联网可比，其核心在于对物理世界规律的深刻把握和运用。打造工业AI的“操作系统”，绝非将消费端的成功经验简单移植那般简单。真正的难点，不在于捆绑软硬件，而在于如何让AI真正理解并尊重钢铁是怎样炼成的、芯片是如何雕刻的、化工厂的管道里流淌着怎样的逻辑。这场战役的决胜点，或许不在通用的算力与软件平台上，而在一个个行业深处，那些沉默的物理公式与老师傅们的经验里。作者：孙健","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"corporation","news_rank":0,"symbols":[],"gpt_button":0,"need_auth":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":0,"favoriteSize":0,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 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