
究竟是先有鸡还是先有蛋?放在AI领域,问题则变成:是先有投资还是先有营收?
据《华尔街日报》和美国消费者新闻与商业频道(CNBC)报道,英伟达将为OpenAI位于俄亥俄州派克县的拟建数据中心园区提供最高1050亿美元担保,低于此前考虑的约2500亿美元担保额度。
这笔交易至少经过两轮调整才敲定最终金额:《华尔街日报》8月14日报道称,英伟达已将担保额度下调至“1200亿美元以内”,随后双方于周一签署合作协议,最终确定为1050亿美元。英伟达在与公告相关向美国证券交易委员会(SEC)提交的文件中披露最终数字——“合计支付义务”上限为1050亿美元。合作协议已于周一签署。担保规模大幅缩减,折射出AI投资者长期以来的顾虑:AI生态系统中的资金循环问题。
英伟达和OpenAI均未回应《财富》杂志的置评请求。
俄亥俄州数据中心项目成为一块试金石:它将检验AI热潮能否创造足够的外部营收,以证明由AI行业内部资金支撑的巨额投入是合理的。市场已释放出担忧这笔交易的信号。7月,有报道称英伟达或将提供高达2500亿美元担保,受投资者对循环融资的担忧情绪影响,英伟达股价盘中下跌约4.5%。
路透社也指出,尽管市场表现亮眼,但投资者仍担忧AI投资的可持续性。他们愈发关注巨额资本开支、持续攀升的债务,以及回报的不确定性。
英伟达的资金安排旨在帮助软银支持的基建开发商SB Energy获取融资:为部分租赁和电力支付提供支持;倘若OpenAI违约,为部分已完工基础设施的资产价值提供担保。这种交易结构大幅降低了英伟达的财务风险敞口。
担保额度缩水之际,英伟达正面临越来越多的质疑:这家全球AI芯片龙头正日益频繁地为最终会采购自家芯片的基础设施提供融资,形成特殊融资模式。这种自我融资循环已持续多年:英伟达一方面投资采购其硬件的AI企业与数据中心运营商,另一方面推出各类融资方案,以帮助客户更轻松地获取算力资源。
上周,英伟达联合六家大型金融机构推出算力融资平台,目标是为AI基础设施筹集超5000亿美元的第三方资金,这一举措近期还获得了监管层面的助力。美国证券交易委员会7月发布的工作人员指导意见认定,部分数据中心债务不适用《多德‑弗兰克法案》证券化规则,该规则要求发起人将部分风险保留在自身账面上,这使英伟达得以更顺畅地调用外部资本,而非自行承担风险敞口。
但英伟达首席执行官黄仁勋并不认同“循环融资”这一说法。他在新闻稿中表示,英伟达“锁定长期算力基础设施,以便OpenAI搭建最高效的AI工厂,该工厂可反复迭代升级,每一代新硬件都能带来更高的智能水平与更优的经济效益”。
在俄亥俄州项目中,OpenAI将向SB Energy租赁数据中心,租期最长可达20年,而英伟达将成为初始阶段的独家芯片供应商。该园区最终算力预计高达8吉瓦。英伟达还将向SB Energy投资15亿美元。
OpenAI在一份说明中表示:“首期800兆瓦算力预计将于2028年投入使用,主要依托现有AEP基础设施。后续扩建需新建并网发电厂(含天然气发电机组),同时配套建设输电线路及相关基础设施。”
SB Energy计划在美国能源部铀浓缩工厂旧址建设该园区,规划配套约9.2吉瓦天然气发电产能,为更广泛的开发提供支撑。软银与SB Energy预计还将追加数十亿美元投资,用于区域电力基础设施建设。
英伟达图形处理器(GPU)已成为全球众多顶尖AI模型训练和运行的主力计算硬件。与中央处理器(CPU)不同,GPU可同时执行大量计算,高度契合机器学习系统使用的矩阵运算。英伟达还围绕芯片搭建包括CUDA编程平台在内的软件生态,使其硬件深度嵌入AI应用的开发流程。
英伟达在投资者资料中,将与OpenAI的合作定位为一体化基础设施服务,涵盖架构、芯片、系统、网络、数据中心、软件、运营和融资。英伟达称,每吉瓦基础设施需投入约500亿至600亿美元,而OpenAI需将未来营收持续投入,以支撑项目建设。
这张错综复杂的交易网络并不局限于OpenAI和英伟达,还涉及与微软、甲骨文、软银、Coreweave等多家企业的合作,以为模型训练与运行锁定充足算力。各方主要通过相互投资、采购算力、共建基础设施等方式深度绑定。
OpenAI表示:“我们拟部署该算力资源,满足高级AI日益增长的需求,巩固前沿AI实验室的领先地位,并切实履行机构使命。”(财富中文网)
译者:中慧言-王芳
究竟是先有鸡还是先有蛋?放在AI领域,问题则变成:是先有投资还是先有营收?
据《华尔街日报》和美国消费者新闻与商业频道(CNBC)报道,英伟达将为OpenAI位于俄亥俄州派克县的拟建数据中心园区提供最高1050亿美元担保,低于此前考虑的约2500亿美元担保额度。
这笔交易至少经过两轮调整才敲定最终金额:《华尔街日报》8月14日报道称,英伟达已将担保额度下调至“1200亿美元以内”,随后双方于周一签署合作协议,最终确定为1050亿美元。英伟达在与公告相关向美国证券交易委员会(SEC)提交的文件中披露最终数字——“合计支付义务”上限为1050亿美元。合作协议已于周一签署。担保规模大幅缩减,折射出AI投资者长期以来的顾虑:AI生态系统中的资金循环问题。
英伟达和OpenAI均未回应《财富》杂志的置评请求。
俄亥俄州数据中心项目成为一块试金石:它将检验AI热潮能否创造足够的外部营收,以证明由AI行业内部资金支撑的巨额投入是合理的。市场已释放出担忧这笔交易的信号。7月,有报道称英伟达或将提供高达2500亿美元担保,受投资者对循环融资的担忧情绪影响,英伟达股价盘中下跌约4.5%。
路透社也指出,尽管市场表现亮眼,但投资者仍担忧AI投资的可持续性。他们愈发关注巨额资本开支、持续攀升的债务,以及回报的不确定性。
英伟达的资金安排旨在帮助软银支持的基建开发商SB Energy获取融资:为部分租赁和电力支付提供支持;倘若OpenAI违约,为部分已完工基础设施的资产价值提供担保。这种交易结构大幅降低了英伟达的财务风险敞口。
担保额度缩水之际,英伟达正面临越来越多的质疑:这家全球AI芯片龙头正日益频繁地为最终会采购自家芯片的基础设施提供融资,形成特殊融资模式。这种自我融资循环已持续多年:英伟达一方面投资采购其硬件的AI企业与数据中心运营商,另一方面推出各类融资方案,以帮助客户更轻松地获取算力资源。
上周,英伟达联合六家大型金融机构推出算力融资平台,目标是为AI基础设施筹集超5000亿美元的第三方资金,这一举措近期还获得了监管层面的助力。美国证券交易委员会7月发布的工作人员指导意见认定,部分数据中心债务不适用《多德‑弗兰克法案》证券化规则,该规则要求发起人将部分风险保留在自身账面上,这使英伟达得以更顺畅地调用外部资本,而非自行承担风险敞口。
但英伟达首席执行官黄仁勋并不认同“循环融资”这一说法。他在新闻稿中表示,英伟达“锁定长期算力基础设施,以便OpenAI搭建最高效的AI工厂,该工厂可反复迭代升级,每一代新硬件都能带来更高的智能水平与更优的经济效益”。
在俄亥俄州项目中,OpenAI将向SB Energy租赁数据中心,租期最长可达20年,而英伟达将成为初始阶段的独家芯片供应商。该园区最终算力预计高达8吉瓦。英伟达还将向SB Energy投资15亿美元。
OpenAI在一份说明中表示:“首期800兆瓦算力预计将于2028年投入使用,主要依托现有AEP基础设施。后续扩建需新建并网发电厂(含天然气发电机组),同时配套建设输电线路及相关基础设施。”
SB Energy计划在美国能源部铀浓缩工厂旧址建设该园区,规划配套约9.2吉瓦天然气发电产能,为更广泛的开发提供支撑。软银与SB Energy预计还将追加数十亿美元投资,用于区域电力基础设施建设。
英伟达图形处理器(GPU)已成为全球众多顶尖AI模型训练和运行的主力计算硬件。与中央处理器(CPU)不同,GPU可同时执行大量计算,高度契合机器学习系统使用的矩阵运算。英伟达还围绕芯片搭建包括CUDA编程平台在内的软件生态,使其硬件深度嵌入AI应用的开发流程。
英伟达在投资者资料中,将与OpenAI的合作定位为一体化基础设施服务,涵盖架构、芯片、系统、网络、数据中心、软件、运营和融资。英伟达称,每吉瓦基础设施需投入约500亿至600亿美元,而OpenAI需将未来营收持续投入,以支撑项目建设。
这张错综复杂的交易网络并不局限于OpenAI和英伟达,还涉及与微软、甲骨文、软银、Coreweave等多家企业的合作,以为模型训练与运行锁定充足算力。各方主要通过相互投资、采购算力、共建基础设施等方式深度绑定。
OpenAI表示:“我们拟部署该算力资源,满足高级AI日益增长的需求,巩固前沿AI实验室的领先地位,并切实履行机构使命。”(财富中文网)
译者:中慧言-王芳
What came first—the chicken or the egg? Or in AI’s case, the investment or the revenue?
Nvidia is guaranteeing up to $105 billion for OpenAI’s planned data center campus in Pike County, Ohio, coming in lower than the roughly $250 billion guarantee it was considering, according to reporting by the Wall Street Journal and CNBC.
The deal moved through at least two known checkpoints before landing at its final size: the Journal reported August 14 that Nvidia had already cut the guarantee to “less than $120 billion,” before the companies settled on $105 billion when the partnership was signed Monday. Nvidia disclosed the final figure—an “aggregate payment obligation” capped at $105 billion—in an SEC filing tied to the announcement. The partnership deal was signed yesterday. The reduction represents a recurring concern among AI investors—the circular cycle of money in the AI ecosystem.
Nvidia and OpenAI did not respond to requests for comment from Fortune.
The Ohio data center is a test of whether the AI boom can generate enough outside revenue to justify the spending being financed from within the AI industry. There is already evidence of market concern from the deal. When reports surfaced in July that Nvidia could guarantee as much as $250 billion, the company’s shares fell about 4.5% intraday from investor reaction to concerns of circular financing.
Reuters also noted anxiety about the sustainability of AI investment remains despite record market performance, with investors increasingly focused on enormous capital expenditures, rising debt and uncertainty over when that spending will generate returns.
Nvidia’s funding is designed to help SB Energy, the SoftBank-backed company developing the campus, secure financing by supporting certain lease and power payments and guaranteeing the value of parts of the completed infrastructure if OpenAI were to default. The structure of the deal substantially reduces Nvidia’s financial exposure to risk.
The rollback comes as Nvidia faces growing questions about a financing model in which the world’s dominant AI-chip maker is increasingly helping finance the infrastructure that ultimately creates the demand for its own chips. The self-funding cycle has been ongoing for years—Nvidia has invested in AI companies and data center operators that purchase its hardware, while also developing financing arrangements intended to make it easier for those customers to acquire more computing capacity.
Last week, Nvidia partnered with six major financial institutions to launch compute-financing platforms targeting more than $500 billion in third-party funding for AI infrastructure—a push that recently got a regulatory tailwind. SEC staff guidance issued in July concluded that certain data-center debt falls outside Dodd-Frank securitization rules requiring sponsors to retain a share of the risk on their own books, making it easier for Nvidia to mobilize outside capital rather than carry the exposure itself.
But Nvidia CEO Jensen Huang disputes the circular financing model. Huang said in a press release the company was “securing long-lived infrastructure for Nvidia compute so OpenAI can deploy the most productive AI factories that can be upgraded repeatedly with each new generation delivering more intelligence and better economics.”
In the Ohio project, OpenAI will lease the data center from SB Energy for as long as 20 years, while Nvidia will be the exclusive chip provider for the initial phase. The campus is ultimately expected to reach as much as 8 gigawatts of computing capacity, and Nvidia is also investing $1.5 billion in SB Energy.
“The first 800 megawatts are expected to become available in 2028 largely using existing AEP infrastructure,” OpenAI shared in a note. “Further development will require new power plants connected to the grid, including natural gas generation, as well as new transmission lines and associated infrastructure.”
SB Energy plans to build the campus at a former US Department of Energy uranium-enrichment site, with approximately 9.2 gigawatts of natural-gas generation planned to support the broader development. SoftBank and SB Energy are expected to invest billions more in regional power infrastructure.
Nvidia’s graphics processing units, or GPUs, have become the primary computing workhorse for training and running many of the world’s most advanced AI models. Unlike CPUs, GPUs can perform many numbers of calculations simultaneously, making them well-suited to the matrix operations used by machine-learning systems. Nvidia also built a software ecosystem around its chips, including its CUDA programming platform, making its hardware deeply embedded in the development of AI applications.
Nvidia’s investor materials described the OpenAI partnership as an integrated infrastructure offering encompassing architecture, chips, systems, networking, data centers, software, operations and financing. Nvidia said each gigawatt of infrastructure would require roughly $50 billion to $60 billion in total spending, while OpenAI would need to reinvest future revenue to fund its buildout.
The web of deals extends past OpenAI and Nvidia, with partnerships with Microsoft, Oracle, SoftBank, Coreweave and other companies to secure computing capacity to train and operate its models. Many of these arrangements involve companies simultaneously investing, purchasing computing capacity, and building infrastructure from one another.
“We expect to use this capacity to meet growing demand for advanced AI and maintain our lead as the frontier AI research laboratory in pursuit of our mission,” OpenAI said.