郭晨凯 制图 ◎记者 李兴彩 春节期间，算力产业链新闻不断。OpenAI"大幅下调"算力投资，引发广泛关注和讨论；Meta与英伟达 达成一项价值数十亿美元的芯片采购协议；Taalas芯片的异军突起引人瞩目…… 不过，在AI应用加速落地的背景下，产业链公司对算力结构、AI大模型乃至于商业模式的需求，都将 发生变化，AI推理算力、国产AI芯片的投资机遇值得重点关注。 算力领域新闻多 产业链景气持续 2月21日，OpenAI宣布，将2030年前的AI基础设施支出目标由1.4万亿美元下调至6000亿美元，引发广 泛关注。知情人士表示，该6000亿美元为纯算力专项支出，聚焦芯片采购与租赁。与此同时，OpenAI 仍在推进超千亿美元的融资，其中90%资金将来自英伟达、软银、亚马逊等战略投资者。 OpenAI CEO山姆·奥特曼于2025年11月演讲中提出，2030年前在AI基础设施上投入约1.4万亿美元，用于 构建全球领先的算力体系，这一广义远景涵盖芯片、电力、土地、数据中心建设等全产业链投入。 对于OpenAI"大幅下调"投资预算，业界给出整体上较为正面的评价。该事件短期情绪上可能利空英伟 达产业链，但长期来看，这意味 ...

Group 1 - Nvidia and Meta have announced a multi-year, multi-billion dollar chip procurement agreement, where Meta will purchase millions of Nvidia's latest AI acceleration chips, including the upcoming "Vera Rubin" series [1][3] - Meta's CEO Mark Zuckerberg stated that the company plans to invest up to $135 billion in AI infrastructure by 2026, nearly double its spending in 2025 [3] - Despite challenges in its own AI chip development, Meta continues to rely on Nvidia's established solutions due to technical challenges and deployment delays in its self-developed AI chip projects [3] Group 2 - The transaction highlights a shift in AI computing focus from "model training" to the "inference" phase, with Nvidia's CEO Jensen Huang adjusting the product strategy to sell CPUs as standalone products rather than integrated with GPUs [3] - The growing demand for efficient, low-latency inference capabilities is driving this change in hardware architecture, as noted by industry analysts [3]