9月26日，黄仁勋在英伟达公司，与顶级风投Altimeter Capital的创始人Brad Gerstner、合伙人Clark Tang 展开了一场长达1小时44分钟的深入对话。 这场对话的信息量巨大，上一篇文章：芯片免费也没用？黄仁勋自信背后，算力战争的终极武器究竟是 什么？我们从芯片、算力和cuda生态的视角提炼重点，今天我们从完整的104分钟里为你提炼出这位"AI 军火之王"对未来最底层的思考逻辑。 这场对话中，黄仁勋系统性地解释了华尔街与硅谷之间存在的巨大认知分歧，并详细拆解了英伟达看似 坚不可摧的商业护城河，以及他对全球人工智能竞赛、大国博弈和未来社会形态的完整思考。 我们正处在巨大的认知分歧之中 一年前，当市场还在为预训练模型的投入是否过剩而担忧时，黄仁勋就说过，推理的增长不是百倍千 倍，而是十亿倍。一年后，他再次声明，自己当初的预测"低估了"。 这种低估源于一个根本性的变化，人工智能的扩展定律已经从一个变成了三个。 第一个是"预训练"，这是大家熟知的，用海量数据喂养大模型。第二个是"训练后"，黄仁勋将其比作人 工智能在"练习"，通过不断的推理和尝试，直到掌握某项技能，这背后是复杂的强化学习过程 ...

公司研究 黄仁勋深度访谈：解读英伟达"护城河"新维度 黄仁勋深度访谈：解读英伟达"护城河"新维度 事件：近日，英伟达（NVDA.O）创始人兼首席执行官黄仁勋受邀 出席「Bg2 Pod」双周对话节目。其间，黄仁勋就当前 AI 行业的竞 争格局、英伟达的护城河以及与 OpenAI 的合作关系等进行了深度 解读。 看好 AI 资本开支增长 在本次访谈中，黄仁勋仍对全球人工智能资本开支持续增长持乐观态 度。他指出，若想实现人工智能为全球 GDP 贡献 10 万亿美元增量价值 的目标，全球每年需投入约 5 万亿美元的资本开支，以支撑能够产生相 应价值的海量 Token。这部分价值的创造机制已不再依赖传统软件，而 是依赖于 AI 系统持续运转、处理海量数据的能力，背后亟需能够承载 庞大算力需求的"AI 工厂"作为核心基础设施。目前，全球云厂商和 科技巨头正全力抢占 AI 基础设施（AI Infra）这一战略制高点。 英伟达的护城河：比三年前"更宽" 面对近期市场对英伟达高增长的可持续性、竞争格局及"循环营收"的 核心质疑，黄仁勋表示公司定位已从"芯片公司"彻底升维至"AI 基 础设施提供商"，其长期增长建立在三大核心基石 ...

Core Viewpoint - The discussion emphasizes the exponential growth potential of AI, particularly in reasoning capabilities, which is expected to be a billion-fold increase, marking the onset of a new industrial revolution [8][3]. Group 1: AI Infrastructure and Investment - NVIDIA's investment in OpenAI is seen as a strategic bet on a future giant, with expectations that OpenAI could become a trillion-dollar company [13][14]. - The projected annual capital expenditure for AI infrastructure could reach $5 trillion globally, reflecting the immense growth potential in this sector [5][32]. - NVIDIA's equity investments are not tied to procurement but are viewed as opportunities to invest in future leaders [51][53]. Group 2: AI Evolution and Market Dynamics - The transition from general computing to accelerated computing and AI is inevitable, with traditional CPU-based systems being replaced by GPU-driven infrastructures [23][25]. - The AI market is expected to grow significantly, with estimates suggesting AI-related revenues could reach $1 trillion by 2030 [39][21]. - The integration of AI into various applications, such as search engines and recommendation systems, is driving demand for advanced computing capabilities [25][40]. Group 3: Competitive Landscape and Barriers - NVIDIA's competitive edge lies in its ability to execute extreme collaborative design, optimizing models, algorithms, systems, and chips simultaneously [6][64]. - The barriers to entry in the AI infrastructure market are increasing due to the high costs associated with chip production and the need for extensive collaboration [71][70]. - Trust in NVIDIA's delivery capabilities is crucial for clients to commit to large-scale orders, reinforcing its market position [74][72]. Group 4: Future Outlook and Technological Integration - The future of AI is envisioned to include the integration of robotics and AI, leading to personal AI companions for individuals [106][105]. - The potential for AI to enhance human intelligence and productivity is significant, with projections indicating that AI could contribute up to $50 trillion to global GDP [29][30]. - The rapid evolution of AI technologies necessitates continuous innovation and adaptation within the industry [61][62].

以下文章来源于明亮公司 ，作者主编24小时在线 明亮公司 . 追踪新商业、好公司，提供一手情报与领先认知。 近期，英伟达（NVDA.US）投资"出手"频繁，先是宣布50亿美元投资英特尔，随后斥资至多1000亿 美元投资OpenAI，而受此前OpenAI与甲骨文的合作，市场均在股价层面给予了积极反馈。 但市场也出现了质疑声音——称英伟达、OpenAI与甲骨文存在"收入循环"，财务数字"操作"大于实 际营收。 9月25日，在播客BG2最新一期节目中，BG2主播、Altimeter Capital创始人Brad Gerstner， Altimeter Capital合伙人Clark Tang与英伟达CEO黄仁勋展开了一次对话。黄仁勋在对话中回应了 当下市场的关心的问题。 黄仁勋认为，投资OpenAI实际上是一个很好的机会，并认为OpenAI将是下一家数万亿美元级别的 Hyperscaler。 此外，黄仁勋也特别解释了为什么ASIC芯片并不完全和英伟达GPU是竞争关系——因为英伟达是AI 基础设施提供商，其提供的能力范围已经不仅仅是硬件和软件层面，也包括其不断迭代的速度、规模 优势带来的可靠性，以及整体能源效率等综合 ...

以下文章来源于明亮公司 ，作者主编24小时在线 本文来自微信公众号： 明亮公司 ，作者：MD，原文标题：《黄仁勋最新访谈：英伟达投资OpenAI 不是签署大额订单的前提》，题图来自：视觉中国 近期，英伟达 （NVDA.US） 投资"出手"频繁，先是宣布50亿美元投资英特尔，随后斥资至多1000 亿美元投资OpenAI，而受此前OpenAI与甲骨文的合作，市场均在股价层面给予了积极反馈。 但市场也出现了质疑声音——称英伟达、OpenAI与甲骨文存在"收入循环"，财务数字"操作"大于实 际营收。 9月25日，在播客BG2最新一期节目中，BG2主播、Altimeter Capital创始人Brad Gerstner， Altimeter Capital合伙人Clark Tang与英伟达CEO黄仁勋展开了一次对话。黄仁勋在对话中回应了当 下市场关心的问题。 黄仁勋认为，投资OpenAI实际上是一个很好的机会，并认为OpenAI将是下一家数万亿美元级别的 Hyperscaler。 此外，黄仁勋也特别解释了为什么ASIC芯片并不完全和英伟达GPU是竞争关系——因为英伟达是AI 基础设施提供商，其提供的能力范围已经不仅仅是 ...

AI时代，快人一步~ 以下文章来源于硬AI ，作者专注科技产研的 硬AI . 作者 | 硬 AI 编辑 | 硬 AI 近日，英伟达创始人兼CEO黄仁勋做客「Bg2 Pod」双周对话节目，与主持人Brad Gerstne和Clark Tang进行了一场广泛的对话。 硬·AI 对谈中，黄仁勋谈及了和OpenAI价值1000亿美元的合作，并就AI竞赛格局、主权AI前景等主题发表了自己的看法。 黄仁勋表示，现在的AI竞争比以往任何时候都激烈，市场已从简单的"GPU"演变为复杂的、持续进化的"AI工厂"，需要处理多样化的工作负载和呈指数级增长的推 理任务。 他预计，如果未来AI为全球GDP带来10万亿美元的增值，那么背后的AI工厂每年的资本支出需要达到5万亿美元级别。 谈及和OpenAI的合作，黄仁勋表示，OpenAI很可能会成为下一个万亿美元级别的超大规模公司，唯一的遗憾是没有早点多投资一些，"应该把所有钱都给他们"。 以下为对谈的亮点内容： • OpenAI想和英伟达建立起类似于马斯克和X那样的"直接关系"，包括直接的工作关系和直接的采购关系。 • 即使不考虑AI创造的新机会，仅仅是AI改变了做事方式就有巨大价值。 ...

他预计，如果未来AI为全球GDP带来10万亿美元的增值， 那么背后的AI工厂每年的资本支出需要达到5 万亿美元级别。 谈及和OpenAI的合作，黄仁勋表示， OpenAI很可能会成为下一个万亿美元级别的超大规模公司，唯一 的遗憾是没有早点多投资一些，"应该把所有钱都给他们"。 在AI商业化前景方面，黄仁勋预计， 未来5年内，AI驱动的收入将从1000亿美元增至万亿美元级别。 关于ASIC的竞争，英伟达放话， 即使竞争对手将芯片价格定为零，客户仍然会选择英伟达，因为他们 的系统运营成本更低。 以下为对谈的亮点内容： 近日，英伟达创始人兼CEO黄仁勋做客「Bg2 Pod」双周对话节目，与主持人Brad Gerstne和Clark Tang 进行了一场广泛的对话。 对谈中，黄仁勋谈及了和OpenAI价值1000亿美元的合作，并就AI竞赛格局、主权AI前景等主题发表了 自己的看法。 黄仁勋表示，现在的AI竞争比以往任何时候都激烈， 市场已从简单的"GPU"演变为复杂的、持续进化 的"AI工厂"，需要处理多样化的工作负载和呈指数级增长的推理任务。 这必须通过他们的资本、通过股权融资和能够筹集的债务来资助。 未来5年内， ...

Core Viewpoint - The AI competition is more intense than ever, evolving from simple GPU markets to complex AI factories that require significant capital investment to support exponential growth in workloads and inference tasks [2][4][6]. Group 1: AI Market Dynamics - The collaboration between Nvidia and OpenAI is expected to create a trillion-dollar company, with Nvidia expressing regret for not investing more earlier [3][21]. - Nvidia anticipates that AI-driven revenue will grow from $100 billion to $1 trillion in the next five years, indicating a high probability of this growth [4][40]. - The global demand for AI infrastructure is projected to require annual capital expenditures of around $5 trillion to support the anticipated $10 trillion increase in global GDP from AI [6][36]. Group 2: Competitive Landscape - Nvidia claims that even if competitors offer chips for free, customers will still prefer Nvidia systems due to lower total operating costs [7][4]. - The company emphasizes that the AI industry is not a zero-sum game, suggesting that AI will create more jobs and opportunities rather than simply displacing existing ones [8]. - Nvidia's competitive advantage lies in its total cost of ownership (TCO) and the ability to provide superior performance per watt compared to other chips [13][7]. Group 3: Future Projections - The integration of AI with robotics is expected to yield significant advancements in the next five years, enhancing productivity across various sectors [14]. - Nvidia predicts that AI will account for approximately 55-65% of global GDP, translating to about $50 trillion, as AI technologies become integral to business operations [13][34]. - The transition from traditional computing to accelerated computing is seen as a fundamental shift, with AI expected to drive substantial changes in how tasks are performed [32][34]. Group 4: Infrastructure and Investment - Nvidia is actively involved in building AI infrastructure in collaboration with OpenAI, which includes significant investments in data centers and AI factories [24][26]. - The company is preparing for a massive increase in demand for AI capabilities, with a focus on ensuring that its supply chain can meet future needs [43][44]. - Nvidia's strategy includes a commitment to continuous innovation and collaboration with partners to enhance AI capabilities and infrastructure [56][58].

Core Insights - OpenAI is likely to become the next trillion-dollar company, with AI-driven revenue projected to grow from $100 billion to $1 trillion within the next five years [1][4][10] - NVIDIA's partnership with OpenAI, involving a $100 billion investment, aims to support the establishment of OpenAI's autonomous AI infrastructure, positioning it as a major player in the AI market [3][10][11] - The shift from general computing to accelerated computing marks the end of Moore's Law, creating significant growth opportunities for NVIDIA in the global computing market [3][17][18] - AI is expected to contribute trillions to global GDP, enhancing human intelligence and creating new industries and applications [3][20][25] - NVIDIA's competitive advantage lies in its "extreme co-design" approach, which integrates chip, software, and system design to deliver exponentially improved performance [3][49][51] AI Growth and Economic Impact - The introduction of a new reasoning law in AI, emphasizing deep thinking before answering, is expected to lead to exponential growth in reasoning capabilities [3][8][9] - AI is projected to significantly enhance productivity and create new job opportunities, rather than eliminate existing jobs [3][20][25] - The potential market for AI infrastructure is estimated to reach $5 trillion, driven by the need for AI to enhance global economic activities [21][22][25] NVIDIA's Strategic Positioning - NVIDIA is transitioning from a GPU supplier to an AI infrastructure builder, integrating various ASICs to meet diverse AI workload demands [3][10][11] - The company's system-level design provides significant cost advantages, ensuring that even if competitors offer ASICs for free, NVIDIA's total cost of ownership remains lower [3][10][11] - NVIDIA's annual release cycle and deep collaboration with the supply chain enhance its ability to deliver high-performance products, creating a formidable competitive barrier [3][41][54] Market Dynamics and Future Outlook - The AI market is experiencing a dual exponential growth driven by increasing user numbers and the computational demands of AI applications [3][13][28] - The transition from CPU to GPU for AI applications is reshaping the infrastructure landscape, with traditional computing methods being replaced by AI-driven solutions [3][18][30] - Concerns about potential oversupply or market bubbles are mitigated by the ongoing demand for AI capabilities, as companies increasingly rely on AI for their operations [3][26][32]

硬·AI 作者 | 硬 AI 编辑 | 硬 AI 近日，英伟达创始人兼CEO黄仁勋做客「Bg2 Pod」双周对话节目，与主持人Brad Gerstne和Clark Tang进行了一场广泛的对话。 对谈中，黄仁勋谈及了和OpenAI价值1000亿美元的合作，并就AI竞赛格局、主权AI前景等主题发表了自己的看法。 黄仁勋表示，现在的AI竞争比以往任何时候都激烈，市场已从简单的"GPU"演变为复杂的、持续进化的"AI工厂"，需要处理多样化的工作负载和呈指数级增长的推 理任务。 他预计，如果未来AI为全球GDP带来10万亿美元的增值，那么背后的AI工厂每年的资本支出需要达到5万亿美元级别。 谈及和OpenAI的合作，黄仁勋表示，OpenAI很可能会成为下一个万亿美元级别的超大规模公司，唯一的遗憾是没有早点多投资一些，"应该把所有钱都给他们"。 以下为对谈的亮点内容： • OpenAI想和英伟达建立起类似于马斯克和X那样的"直接关系"，包括直接的工作关系和直接的采购关系。 • 假设AI为全球GDP带来10万亿美元的增值，而这10万亿美元的Token生成有50%的毛利率，那么其中5万亿美元需要一个工厂，需要一个AI基础设 ...