从5万亿参数到20GW云：阿里押注AI基础设施的下一站

同花顺09-28 16:43

阿里巴巴（BABA）正在把大模型竞争的尺度继续向上推。9月22日云栖大会上，阿里巴巴（BABA）CEO吴泳铭表示，Qwen团队正推进模型架构与数据优化研究，计划训练参数规模达到5万亿至10万亿的全新模型，目标是处理更复杂、更长程的任务，并向ASI，即人工超智能方向探索。这仍是一个规划目标，并不代表模型已经完成或达到预期能力。但从阿里同时公布的芯片、云和数据中心计划看，5万亿至10万亿参数并非孤立的...

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vernova（GEV）积压订单及预留产能达到116GW，2030年产能已经售罄，2031年产能也有超过一半被预订。相关预测和订单情况仍属于机构报告及市场信息，但它们说明，AI算力扩张的瓶颈可能逐步从芯片延伸到电力和能源（850101）设备。三、模型变大，不等于企业应用自动成熟阿里云智能集团副总裁霍嘉在云栖大会期间接受媒体采访时提到，企业AI项目失败，很多时候并非模型能力不足，而是场景选择错误、数据质量被高估，或者仍沿用传统信息化项目的实施方式。他将客户分为四类：AI原生客户、高科技客户、企业级客户和政府客户。前两类通常有明确需求，购买Token后即可开始使用；后两类则更看重投入产出比，需要先证明AI确实有价值。霍嘉认为，企业级客户落地较慢，主要受AI人才不足、可复制案例有限，以及模型和工程方法快速变化等因素影响。企业拥有数据，也不代表这些数据可以直接服务于智能体应用。霍嘉曾将这一问题概括为“IT Data不等于AI Data”，在应用阶段又进一步提出“IT Data不等于Agentic Data”。一套系统里的数据，只有经过整理、授权和流程适配，才能进入Agent运行环境。项目规模同样需要重新评估。霍嘉提到，一家大型企业曾计划为每天仅有一百多笔交易的B2B电商平台设计AI方案。按照他的判断，人工处理这些交易只需几分钟到几小时，贸然引入复杂AI系统，未必能形成足够收益。因此，阿里云团队会主动拒绝部分场景，或者建议客户暂缓实施。四、竞争焦点或从“训练模型”转向“把模型用起来”为了提高落地效率，阿里云正在尝试让工程人员更早进入客户现场。霍嘉所介绍的FDE，即前置部署工程师模式，强调在售前阶段验证场景、技术可行性和ROI，再把成熟方案做成生产级系统。与传统先确定范围、签署项目文件再交付的方式相比，这种方法更接近边验证、边开发、边迭代。阿里云并未将FDE定位为独立的服务生意。霍嘉表示，团队的核心考核是能否带动产品，阿里也不是一家以服务为主的公司。围绕FDE的长期商业化，阿里云更倾向于两类模式：产品商业模式，或面向重点客户的长期服务合同。结果付费，即Result as a Service（SCI），也被视为一种可能的方向，但其能否成为普遍模式仍待市场验证。对阿里而言，训练5万亿至10万亿参数模型的意义，可能不只是刷新模型规模。它将同时检验自研芯片能否支撑大规模训练与推理，云基础设施能否持续扩张，以及企业客户是否愿意为更强的模型能力支付成本。Token消耗增长、价格上行，显示AI原生和高科技客户的需求正在加速；企业级应用则仍需要逐个场景验证。因此，阿里的这项计划可能推动算力、芯片、服务器、网络、能源（850101）和云服务形成更紧密的协同，也可能让行业更清楚地看到：大模型竞争的终点并不只是参数量，真正决定商业价值的，还包括基础设施效率、数据可用性和应用结果。5万亿至10万亿参数模型能否按计划落地、实际能力如何，目前仍需要后续进展来验证。","kind":"highlight","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":false,"editions":null,"column":"","sentiment":"0","news_tag":"productRelease","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":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 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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