记者丨彭新 编辑丨朱益民 2026年国际消费电子展（CES）期间，全球最大的专业技术组织IEEE（电气电子工程师学会）宣布，将 2026年IEEE荣誉勋章（IEEE Medal of Honor）授予英伟达创始人兼CEO黄仁勋，并颁发200万美元奖 金。 作为科技界的最高荣誉之一，IEEE荣誉勋章自1917年设立以来，来表彰对世界产生深远影响的杰出技 术人物。黄仁勋此次获奖，标志着工程界对其在加速计算及人工智能领域开创性贡献的最高认可，其名 字与互联网之父文顿·瑟夫、英特尔创始人罗伯特·诺伊斯以及台积电创始人张忠谋等科技界传奇人物并 列。 IEEE主席兼CEO Mary Ellen Randall在颁奖词中评价称，黄仁勋的领导力和技术远见开启了人类创新的 新时代，从1999年推出首款GPU（图形处理器）开始，他建立的基础设施不仅推动了科学、医学和工程 的进步，更为现代生成式AI的爆发奠定了算力基石。 在位于拉斯维加斯的颁奖现场，黄仁勋在致辞中罕见流露出感性一面，他并没有大谈特谈英伟达的商业 宏图以及AI愿景，而是向工程师这一身份致以深情敬意。 "这个职业是所有职业中最崇高的，用这句话来表达就足够了。"黄仁勋在 ...

2026年国际消费电子展（CES）期间，全球最大的专业技术组织IEEE（电气电子工程师学 会）宣布，将2026年IEEE荣誉勋章（IEEE Medal of Honor）授予英伟达创始人兼CEO黄仁 勋，并颁发200万美元奖金。 作为科技界的最高荣誉之一，IEEE荣誉勋章自1917年设立以来，来表彰对世界产生深远影响 的杰出技术人物。黄仁勋此次获奖，标志着工程界对其在加速计算及人工智能领域开创性贡献 的最高认可，其名字与互联网之父文顿·瑟夫、英特尔创始人罗伯特·诺伊斯以及台积电创始人 张忠谋等科技界传奇人物并列。 IEEE主席兼CEO Mary Ellen Randall在颁奖词中评价称，黄仁勋的领导力和技术远见开启了人 类创新的新时代，从1999年推出首款GPU（图形处理器）开始，他建立的基础设施不仅推动了 科学、医学和工程的进步，更为现代生成式AI的爆发奠定了算力基石。 在位于拉斯维加斯的颁奖现场，黄仁勋在致辞中罕见流露出感性一面， 他并没有大谈特谈英 伟达的商业宏图以及AI愿景，而是向工程师这一身份致以深情敬意。 "这个职业是所有职业中最崇高的，用这句话来表达就足够了。" 黄仁勋在获奖感言中说。他 将工 ...

黄仁勋因其在加速计算领域毕生的远见卓识与开创性贡献而获此殊荣，这些成就推动英伟达走在了技术创新的最前沿。在其引领下，英伟达于 1999年发明了全球首款图形处理器（GPU）——这一突破彻底革新了计算技术，并推动了医学、工程、机器人、自动驾驶汽车、制造业等众多领 域的进步，且已于2025年10月成为全球首家市值突破5万亿美元的企业。黄仁勋在加速计算领域的远见为当今的AI技术与工业革命奠定了基础。 （全球TMT2026年1月7日讯）全球最大的专业技术组织IEEE宣布：英伟达（NVIDIA）创始人兼首席执行官黄仁勋荣获IEEE最高荣誉——2026年 度IEEE荣誉勋章，并获颁200万美元奖金。 ...

Core Insights - The U.S. government has allowed NVIDIA to sell its H200 AI chips to "approved customers" in China and other regions, with a condition of a 25% revenue share to the U.S. government [1] - Jensen Huang, NVIDIA's CEO, expressed uncertainty about the future necessity of CPUs in an AI-driven era, suggesting that GPUs may eventually replace CPUs [1] - NVIDIA's revenue from data center GPUs is projected to surge from $15 billion in 2023 to $115.2 billion in the fiscal year 2025 [1] Industry Trends - The GPU market is experiencing a surge in interest, highlighted by the significant stock price increase of Chinese GPU company Moore Threads on its debut [3] - The demand for GPUs is rising due to the explosion of large model training, but the complete replacement of CPUs by GPUs is debated [4][6] - CPUs remain essential for complex task management, while GPUs excel in parallel computing tasks [4][6] Competitive Landscape - Major tech companies are accelerating the deployment of new GPU clusters, with Alibaba Cloud and Baidu developing their own chips to enhance AI capabilities [7][9] - Amazon and Google are also investing in self-developed chips to reduce dependency on NVIDIA, focusing on efficiency and cost control [9][10] - The shift towards GPU dominance in cloud computing is evident, but companies are also developing their own solutions to avoid being solely reliant on NVIDIA [9][10] Future Directions - The transition of AI tasks from cloud to local devices is reshaping the computing architecture, with GPUs becoming increasingly important in smartphones and PCs [10][11] - The rise of AI PCs emphasizes the importance of GPU performance over traditional CPU metrics [11] - The automotive industry is also leveraging GPUs for real-time data processing in autonomous driving applications [11] Ecosystem Development - CPU manufacturers like Intel and AMD are not retreating; they are adapting by enhancing their AI processing capabilities and developing competitive ecosystems [14][15] - NVIDIA's strength lies in its established ecosystem, particularly with CUDA, which poses challenges for competitors [15] - The competition in the computing sector is shifting towards who can build a comprehensive AI ecosystem, with companies like Huawei making significant strides [15][16]

黄仁勋在访谈中指出，AI竞赛无明确终点线，持续迭代能力比一次性突破更重要，技术进步是渐进 的，所有参与者将共同进化。过去10年AI算力提升10万倍，但这些算力用于让AI更谨慎思考、检验答 案，而非做危险的事。黄仁勋还详细回顾了英伟达多次濒临破产的创业经历，包括1995年技术路线选 择错误、依靠世嘉500万美元投资和台积电张忠谋的信任才得以生存的惊险时刻。 英伟达创始人兼CEO黄仁勋近日在播客节目中进行了一场长达两小时的深度访谈，详细阐述了他对人 工智能竞赛、公司经营以及个人成长的看法。 这位全球市值最高科技公司之一的掌门人，以罕见的坦诚揭示了一个令人意外的事实： 尽管英伟达已 成为AI时代的核心企业，但他每天醒来仍然感到公司"距离倒闭还有30天"。 在谈及当前全球关注的AI竞赛时，黄仁勋提出了与主流观点截然不同的看法。他认为，这场竞赛并非 如外界想象的那样存在一条明确的"终点线"，也不会出现某一方突然获得压倒性优势的局面。相反， 技术进步将是渐进式的，所有参与者都将站在AI的肩膀上共同进化。 他认为， 真正的竞争力在于持续迭代能力，而非一次性突破 。过去10年AI算力提升10万倍，但这些 算力用于让AI更谨慎 ...

Core Insights - The core mechanism of generative AI has fundamentally shifted from data retrieval to learning knowledge structures and performing real-time logical reasoning [4] - Data centers are evolving into new factories that input energy and data to produce intelligent tokens on a large scale [4] - Accelerated computing is allowing Moore's Law to be reborn in a different form [4] - Future programming languages will revert to human natural language, significantly lowering technical barriers and empowering individual creativity [4] Group 1: Transition from Retrieval to Reasoning - The transition from "retrieval" to "reasoning" represents a fundamental change in AI capabilities, where AI generates answers based on learned knowledge rather than retrieving pre-stored responses [6] - Deep learning differs from traditional software development, as it involves training a neural network with vast amounts of input-output examples rather than coding algorithms directly [6][11] Group 2: AI as a New Manufacturing Process - Data centers are described as "AI factories," where the input is electricity and data, and the output is tokens, representing a new form of manufacturing [9] - Energy consumption is a significant challenge for AI expansion, but improving chip efficiency is crucial to meet growing demands without exhausting global energy resources [9][11] Group 3: The Future of Programming - The future of programming will not require learning traditional programming languages; instead, individuals will express their intentions in natural language, making programming accessible to everyone [11] - AI is expected to change job roles rather than eliminate them, as it will allow professionals to focus on core tasks while AI handles routine work [11] Group 4: Accelerated Computing and Moore's Law - Traditional Moore's Law, which states that chip performance doubles every two years, is slowing down, but accelerated computing is reviving it in the context of AI [13][15] - The cost of AI computing has decreased by 100,000 times over the past decade, akin to a revitalized version of Moore's Law [15] Group 5: Company History and Challenges - The company faced a near-bankruptcy situation in 1996, only 30 days away from failure, due to a significant technical error in their gaming chip technology [21] - The CEO's honesty in admitting the failure to a partner led to a crucial financial rescue that saved the company [21][23] Group 6: Leadership and Personal Insights - The CEO emphasizes the importance of experiencing challenges and pain as part of the journey to achieving greatness [33] - The CEO maintains a strong work ethic and a sense of urgency, waking up early to manage responsibilities and staying focused on the present [27][31]

当地时间12月3日，英伟达创始人、首席执行官黄仁勋（Jensen Huang）做客全球最受欢迎的播客节目 之一《The Joe Rogan Experience》，与主持人乔伊·罗根（Joe Rogan）进行了一场长达近2.5个小时的深 度对谈。 黄仁勋在访谈中系统性地回顾了英伟达31年创业史，并对AI发展、能源、就业、技术鸿沟等关键议题 给出明确判断。 他系统复盘了英伟达历史中最惊险的三次濒死时刻，还对当下最受关注的问题给出明确答案：AI算力 大部分用于安全（让模型学会思考、查资料、自纠错）；未来十年AI能耗对大多数人将"微不足道"；技 术鸿沟会大幅缩小；就业不会消失，而是"任务"被取代、"目的"创造新职业；量子计算会来，但后量子 加密也在同步研发；未来6-7年将出现大量小型核反应堆。 以下为此次对话的精简版： 01.绝境逢生：英伟达三次濒死危机与逆袭之路 问：你是如何说服世嘉投资的？ 答：我向世嘉CEO入交昭一郎坦诚技术失效、合同履约无意义的事实，请求将剩余500万美元合同款转 为投资。即便他知晓公司大概率倒闭，仍因对我的认可同意投资，为我们保留了生机。 问：资金耗尽时如何完成芯片开发？ 答：我们放弃传统 ...

Core Viewpoint - NVIDIA's CFO Colette Kress believes there is no bubble in the AI sector and anticipates a significant market transformation by 2030, with data center infrastructure potentially reaching $3 trillion to $4 trillion due to increasing demand for accelerated computing [2]. Group 1: Market Outlook - The majority of NVIDIA's AI chip shipments are aimed at building new data center infrastructure rather than replacing existing equipment [2]. - By 2026, NVIDIA expects to have orders worth $500 billion for its Blackwell and Rubin GPU chips, which exceeds 3.5 trillion [2][4]. Group 2: Partnerships and Investments - NVIDIA is working on a final agreement with OpenAI, with a previous investment of $100 billion aimed at enhancing OpenAI's computing power through the purchase of NVIDIA's AI GPUs [4]. - The collaboration between NVIDIA and OpenAI is expected to be ongoing, contributing to rising stock prices and valuations for both companies, similar to trends seen with Oracle and Amazon [4]. Group 3: Production and Delivery - At the recent GTC conference, NVIDIA's CEO Jensen Huang announced that the company has GPU orders totaling $500 billion, with plans to deliver 20 million units of Blackwell and Rubin architecture GPUs over the next five quarters [4].

Market Overview - US stock market ended a five-day rally with major indices declining: Dow Jones down 427.09 points (0.90%) to 47289.33, Nasdaq down 89.77 points (0.38%) to 23275.92, and S&P 500 down 36.46 points (0.53%) to 6812.63 [3] - The ISM Manufacturing PMI for November fell to 48.2, marking the largest contraction in four months and remaining below the neutral level of 50 for nine consecutive months [3] Oil Market - Crude oil prices increased due to supply concerns following an attack on a Black Sea terminal, with WTI crude rising by $0.77 (1.32%) to $59.32 per barrel and Brent crude up $0.79 (1.27%) to $63.17 per barrel [10] - The Caspian Pipeline Consortium announced a suspension of operations at its Black Sea terminal due to drone attacks, although loading operations at Novorossiysk port continued [10] Nvidia and Synopsys Partnership - Nvidia announced a $2 billion investment in Synopsys, aiming to enhance collaboration in AI and accelerated computing, which will help design and validate smart products more efficiently [4][5] - Nvidia's CEO Jensen Huang emphasized the significance of this partnership for innovation in the design and engineering sectors [5] Semiconductor Sector - Mixed performance in the semiconductor sector with Philadelphia Semiconductor Index down 0.07%, while companies like ASML and NXP Semiconductors saw gains of over 2% [5] - Micron Technology plans to invest $9.6 billion in a new AI memory chip factory in Japan, expected to start production around 2028, supported by substantial government subsidies [7] Large Tech Stocks - Major tech stocks showed mixed results, with Apple up over 1% and Amazon rising 0.28%, while Google, Microsoft, and Facebook experienced declines of over 1% [8]

Market Overview - US stock markets ended a five-day winning streak, with the Dow Jones down 427.09 points (0.90%) at 47289.33, Nasdaq down 89.77 points (0.38%) at 23275.92, and S&P 500 down 36.46 points (0.53%) at 6812.63 [4][5] - The ISM Manufacturing PMI for November dropped to 48.2, marking the largest contraction in four months and remaining below the neutral line for nine consecutive months [6] Oil Market - Oil prices increased, with WTI crude oil rising by $0.77 (1.32%) to $59.32 per barrel and Brent crude oil up by $0.79 (1.27%) to $63.17 per barrel, amid supply concerns following an attack on a Black Sea terminal [16] Nvidia and Synopsys Partnership - Nvidia announced a $2 billion investment in Synopsys, aiming to enhance collaboration in AI and accelerated computing, which will help design and validate smart products more efficiently [8] - Nvidia's CEO Jensen Huang emphasized the significance of this partnership for the design and engineering sector, which is highly computation-intensive [8] Semiconductor Sector Performance - The Philadelphia Semiconductor Index experienced mixed results, with notable gains from ASML (up over 2%) and NXP Semiconductors (up over 2%), while Broadcom saw a decline of over 4% [8] - Morgan Stanley raised Broadcom's target price from $409 to $443, while also increasing Nvidia's target price from $235 to $250 [10] Major Tech Stocks - Major tech stocks showed mixed performance, with Apple rising over 1% and Amazon up 0.28%, while Google, Microsoft, and Facebook all fell by over 1% [12][13]