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"title": "黄仁勋驳斥辉达「循环融资」质疑:公司成长上限是「供应」、不是「需求」",
"shortTitle": "黄仁勋驳斥辉达「循环融资」质疑:公司成长上限是「供应」、不是",
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"description": "辉达执行长黄仁勋驳斥市场对「循环融资」的质疑,强调投资背后有真实合约与营收支撑,并重申AI基础设施需求强劲,算力、电力与资料中心容量才是成长瓶颈。",
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"content": "<p>辉达(<a data-symbol-template=\"USS:NVDA:STOCK:COMMON\" href=\"#\">NVDA-US</a>) 近来大手笔投资AI产业,却也引发市场对「循环融资」的质疑。外界担心,辉达投资AI公司或云端服务商后,这些企业再利用资金购买辉达晶片,可能形成投资与硬体销售彼此推动的循环。对此,辉达执行长黄仁勋在高盛年度科技盛会「Communacopia + Technology Conference」上正面回击,强调相关投资背后都有真实客户合约与收入支撑。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6605105/l/55795a9cc9ea804168ca8300f9918bcc.jpg\" alt=\"黄仁勋驳斥辉达「循环融资」质疑:公司成长上限是「供应」、不是「需求」\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>辉达今年8月宣布与Apollo、贝莱德(<a data-symbol-template=\"USS:BLK:STOCK:COMMON\" href=\"#\">BLK-US</a>) 、黑石(<a data-symbol-template=\"USS:BX:STOCK:COMMON\" href=\"#\">BX-US</a>) 、Brookfield、高盛集团(<a data-symbol-template=\"USS:GS:STOCK:COMMON\" href=\"#\">GS-US</a>) 及KKR(<a data-symbol-template=\"USS:KKR:STOCK:COMMON\" href=\"#\">KKR-US</a>) 等金融机构合作,成立算力融资平台,计划募集超过5000亿美元第三方资金,协助AI模型开发商建设基础设施。</p>\n\n<p>市场部分人士担心,若辉达投资AI公司或云端服务商,而这些企业再使用资金购买辉达硬体,可能形成投资与销售彼此循环的模式。</p>\n\n<p>对此,黄仁勋以公司财务表现反驳相关疑虑。他强调,在辉达投入资金之前,会确认被投资企业手上具有真实合约,且能够从客户取得营收;他所看到的相关合约总额达1000亿美元。</p>\n\n<p>他直言:「我们投入1美元、拿回100美元的回报,这算是循环融资吗?如果这也算,那我们就多做一些。」</p>\n\n<p>高盛研究也认为,辉达提供的财务支持主要是为AI生态系统提供种子资金,最终回报规模以及参与投资者的多元化程度,并不符合「循环融资」的典型定义。</p>\n\n<p>与此同时,辉达、SpaceX(<a data-symbol-template=\"USS:SPCX:STOCK:COMMON\" href=\"#\">SPCX-US</a>) 、Crowdstrike(<a data-symbol-template=\"USS:CRWD:STOCK:COMMON\" href=\"#\">CRWD-US</a>) 等科技巨头高层亦纷纷释放讯号,指出当前AI产业真正的制约因素已从需求转向算力、电力与资料中心容量,相关供应瓶颈可能延续至2028年。</p>\n\n<p>不过,随着超大规模云端业者大举增加资本支出,市场最关注的问题仍在于:这些巨额投资最终能否转化为持续性的企业AI营收。</p>\n\n<h6>黄仁勋:辉达成长上限是供应,不是需求</h6>\n\n<p>黄仁勋重申,AI基础设施市场到2030年可能扩大至3兆至4兆美元。他并再次强调,辉达2027会计年度约70%的年营收成长率,其实是「供应上限」,而非「需求上限」。换言之,如果供应不存在限制,公司营收增速可能更高。</p>\n\n<p>分析师预估,辉达本会计年度营收约4000亿美元,若按照70%的增幅计算,下一年度营收可能达到约6800亿美元。</p>\n\n<p>黄仁勋接受高盛半导体分析师James Schneider访问时指出,AI基础设施需求之所以持续高速成长,主要受到两项重大产业转变推动,包括从检索式运算转向生成式运算,以及摩尔定律逐步失效。</p>\n\n<p>过去的电脑运算主要是从储存空间撷取既有资讯;生成式AI则不同,需要根据使用者提供的上下文即时产生答案,因此必须建立一个持续运作的新运算层。</p>\n\n<p>另一方面,随着电晶体微缩带来的效能提升逐渐放缓,单纯依靠制程进步已不足以满足需求。辉达因此透过CoWoS多晶片封装、NVLink等技术进行更高度的系统整合与扩充。</p>\n\n<p>黄仁勋表示,如果无法实现强大的NVLink与纵向扩充能力,企业将难以在摩尔定律逐渐失去效益的环境下维持竞争力。</p>\n\n<p>此外,他也指出,各家AI实验室都能利用辉达平台建立自身业务,使其在某种程度上与台积电(<a data-symbol-template=\"TWS:2330:STOCK:COMMON\" href=\"#\">2330-TW</a>) 的产业地位相似。</p>\n\n<p>尽管黄仁勋承认从上游封装、晶圆、记忆体,到下游资料中心的电力与选址,都可能成为AI基础设施的扩张障碍,但他认为辉达的生态系规模与顾客可见度是因应这些限制的核心优势。</p>\n\n<h6>SpaceX瞄准AI基建 2027年部署AI卫星</h6>\n\n<p>SpaceX财务长Johnsen则在会议上提出另一套AI基础设施布局。</p>\n\n<p>他表示,SpaceX正在从单纯的火箭发射与卫星营运商,转向整合火箭、电力、算力基础设施、AI模型、客户关系及Starlink连网服务的一体化AI基础设施平台。</p>\n\n<p>Johnsen透露,目前公司算力收益处于每GW 300亿至500亿美元区间的上缘,且本月初已完成一笔新的算力授权协议。</p>\n\n<p>SpaceX目前也进一步提高对营收目标的信心,朝年底实现年化1000亿美元总营收迈进。</p>\n\n<p>在算力规模方面,公司预计2026年底前扩大至超过2GW,2027年底进一步达到5GW至10GW。</p>\n\n<p>此外,SpaceX计划在2027年部署AI卫星,并预期轨道算力成本降至与地面算力相当的时间,将早于先前预期。</p>\n\n<p>Starlink宽频业务则持续成长,其中企业与政府服务表现突出;Starlink Mobile预计于2028年上半年推出。</p>\n\n<p>Johnsen将AI模型、地面算力、Starlink、星舰以及轨道算力串联起来,形成SpaceX未来AI基础设施业务的整体成长架构。</p>\n\n<h6>网路安全成AI新战场 黄仁勋:下一个主要应用场景</h6>\n\n<p>除了算力之外,网路安全也是此次高盛科技大会最受关注的主题之一。</p>\n\n<p>黄仁勋表示,网路安全将成为AI下一个主要应用场景。原因在于,AI加速程式码生成后,不仅能提高开发效率,也可能加快漏洞被发现与利用的速度,进一步推升企业对漏洞修补与安全防护的需求。</p>\n\n<p>目前辉达已与CrowdStrike、思科系统(<a data-symbol-template=\"USS:CSCO:STOCK:COMMON\" href=\"#\">CSCO-US</a>) 及Palantir(<a data-symbol-template=\"USS:PLTR:STOCK:COMMON\" href=\"#\">PLTR-US</a>) 合作,利用Nemotron模型建立红队与蓝队系统。</p>\n\n<p>Palo Alto Networks (<a data-symbol-template=\"USS:PANW:STOCK:COMMON\" href=\"#\">PANW-US</a>) 执行长Nikesh Arora则表示,AI正在加快漏洞发现及攻击复杂程度,企业未来需要整合式安全平台,而非依赖大量彼此分散的供应商。</p>\n\n<p>Palo Alto目前拥有约1.8亿个已部署感测器,每日处理约19PB资料。Arora认为,这些资料将构成公司的资料与训练护城河。他更直言,目前「AI安全产业甚至尚未建立」。</p>\n\n<p>他指出,未来5年预计投入的5兆美元算力资本支出,将带动网路流量大幅增加,而相关流量都需要安全监测。</p>\n\n<p>CrowdStrike执行长George Kurtz则强调,公司累积逾10年的专有标注安全资料是重要竞争壁垒。以公司域专用模型为例,每次活动的修复成本约0.03美元,而尖端模型替代方案约10美元,但两者能达到相近效果。</p>\n\n<p>CrowdStrike新产品Guardian早期需求强劲,Flex协议累计达935笔,弹性承诺总额达23亿美元;上季Flex交易量也较前季增加两倍。</p>\n\n<h6>半导体设备商:产业几乎「售罄」 供应紧张延续</h6>\n\n<p>半导体设备业者同样看好AI基础设施带来的需求。</p>\n\n<p>科林研发(<a data-symbol-template=\"USS:LRCX:STOCK:COMMON\" href=\"#\">LRCX-US</a>) 财务长Doug Bettinger形容,目前产业基本上已经「售罄」,公司管理层眼下更担心无法抓住需求上行,而非准备迎接下行周期。</p>\n\n<p>科林预期,2027年晶圆设备支出(WFE)成长将主要由DRAM带动,其次为先进逻辑与晶圆代工,NAND也将维持稳健成长。</p>\n\n<p>其中,无尘室可用性将成为关键限制,预计至少持续至2027年底。</p>\n\n<p>科林同时已与SpaceX的Terafab计划展开深入合作,并将其形容为「非常大的机会」。公司也宣布将在美国投资30亿美元,用于实验室与工程建设,包括在奥勒冈州新建实验室。</p>\n\n<p>至于中国市场,科林预期今年WFE支出小幅成长,但中国占整体比重将持续下降。</p>\n\n<p>希捷科技(<a data-symbol-template=\"USS:STX:STOCK:COMMON\" href=\"#\">STX-US</a>) 财务长Gianluca Romano则指出,AI基础设施带动的储存需求,加上供给增幅有限,将持续支撑价格上涨。</p>\n\n<p>希捷上季每艾字节价格年增约11%;HAMR技术出货量预计在2026年底以艾字节计算超越PMR,未来几年HAMR预计将占公司出货量约80%至90%。</p>\n\n<h6>高盛:AI是投资超级周期 但最终仍须证明ROI</h6>\n\n<p>高盛科技研究主管James Schneider与欧洲TMT专家Sean Johnstone在会议总结中指出,AI需求正沿着整个科技产业链扩张,市场关注焦点也逐渐从模型能力,转向基础设施规模、电力、投资报酬率(ROI)以及企业实际应用。</p>\n\n<p>高盛银行家认为,目前AI更接近一个投资超级周期,而非泡沫;供应紧张、强劲的算力需求以及加速的产品创新,都使产业基本面仍具建设性。</p>\n\n<p>但市场仍面临利率、地缘政治、政策不确定性及规模效应等宏观挑战。</p>\n\n<p>Johnstone指出,AI需求确实仍在扩张,但投资人接下来需要看到的,是超大规模云端业者能否将目前累积的资本支出与订单,转化为持久的企业AI营收、利润率及现金流。</p>\n\n<p>与此同时,企业客户的算力需求也可能逐渐从追求最大化算力消耗,转向更加重视ROI的算力配置与最佳化。</p>\n\n<p>在电力、记忆体、资料中心建设及容量持续受限的情况下,AI基础设施市场的供需紧张格局,可能一路延续至2028年。</p>\n<div class=\"related-articles seo-links\">\n <h4>相关阅读</h4>\n <ul>\n <li><a href=\"/new/mg/article-3674.html\" title=\"美光Q3财报创高背后5大讯号 CEO透露商业模式正加速转型\">美光Q3财报创高背后5大讯号 CEO透露商业模式正加速转型</a></li>\n <li><a href=\"/new/mg/article-6579.html\" title=\"辉达CUDA神话没松动?SemiAnalysis转赞vLLM、AMD追赶的不只是硬体\">辉达CUDA神话没松动?SemiAnalysis转赞vLLM、AMD追赶的不只是硬体</a></li>\n <li><a 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