We're joining me now for a preview of Nvidia set to report its highly anticipated results after the close. We've got Melissa Otto, head of Visible Alpha Research at S&P Global Market Intelligence. Uh it's good to see you, Melissa.And I know you were back from recent travel. So, welcome back. I believe uh you were traveling recently.So, let's talk about the expectations, consensus expectations going into this uh street looking for a buck 24 per share for Nvidia. Revenue is expected to top 54.6% billion. What ...

Core Insights - NVIDIA has introduced NVQLink, a universal interconnect designed to link quantum processors with advanced accelerated computing, marking a significant advancement in scientific computing [1][11] - Over a dozen supercomputing centers and national research institutions in Asia and Europe are adopting NVQLink, enhancing their capabilities in integrating quantum and classical hardware [2][11] - Jensen Huang, CEO of NVIDIA, emphasized that NVQLink with CUDA-Q is pivotal for the future of supercomputing, enabling the combination of quantum and GPU systems for groundbreaking scientific discoveries [3][11] Technical Specifications - NVQLink delivers 40 petaflops of AI performance at FP4 precision, with a GPU-QPU throughput of 400 Gb/s and a latency of less than four microseconds [3][11] - The architecture allows for tight integration of quantum processors and GPUs, facilitating the development of hybrid quantum-classical applications [4][11] - The system architecture is open and designed in collaboration with global quantum processor builders and supercomputing centers [4][11] Real-World Applications - Quantinuum's Helios QPU will integrate with NVIDIA GPUs through NVQLink, utilizing NVIDIA CUDA-Q for quantum error correction [5][11] - The first real-time use of a scalable decoder for quantum error-correction codes was demonstrated, achieving a reaction time of 67 microseconds, significantly surpassing the Helios' requirement [7][11] - NVQLink's microsecond latencies and high throughput are accessible to developers via real-time APIs in NVIDIA CUDA-Q, enabling easier development of quantum applications [8][11] Global Adoption - Notable supercomputing centers adopting NVQLink include institutions from Japan, Korea, Taiwan, Singapore, Australia, Italy, Denmark, France, the Czech Republic, Germany, the UK, Poland, the UAE, and Saudi Arabia, alongside U.S. national laboratories [12][11]

Core Insights - The article highlights Micron Technology as a compelling investment opportunity in the AI infrastructure sector due to its attractive valuation and significant growth potential [1][3][4] Company Overview - Micron Technology specializes in manufacturing compute and storage memory chips used in various applications, including data centers, personal computers, smartphones, and automotive components [3] - The company reported a 49% year-over-year revenue increase to $37.4 billion and a 537% rise in adjusted earnings to $8.29 per share for fiscal 2025 [4] Valuation Metrics - Micron's trailing earnings multiple stands at 24, while its forward earnings multiple is even more appealing at 14, with a price-to-sales ratio of 7, which is lower than other AI infrastructure stocks [5][6] - Analysts project that Micron's earnings are expected to double in the current fiscal year, indicating strong growth expectations [7] Market Opportunity - The capital spending on data centers is projected to grow at a compound annual growth rate (CAGR) of 40% from 2025 to 2030, potentially reaching between $3 trillion and $4 trillion by the end of the decade [10] - Micron estimates that the high-bandwidth memory (HBM) market revenue could double to $35 billion by 2025, with significant growth potential driven by increased data center capital expenditures [12] Competitive Position - Micron is currently gaining market share in the HBM space, controlling 21% of the market as of Q2, and is expected to increase its share to 23%-24% by the end of the year [14][15] - The company is well-positioned to benefit from the growing demand for HBM due to its partnerships with major AI chip designers and its next-generation HBM offerings [15]

AI与加速计算 - 英伟达在加速计算领域深耕30年，是GPU和CUDA编程模型的发明者，加速计算的时代已经到来 [1] - 英伟达将AI视为其核心价值所在，并认为AI能够提升劳动生产力，促进经济增长 [3] - 英伟达的AI工厂专注于运行AI，与传统数据中心不同 [3] 行业合作与技术发展 - 英伟达与诺基亚建立了重要的合作伙伴关系，合作基于加速计算和AI，旨在引领6G的下一场革命 [2] - 英伟达宣布与17家量子产业公司合作，支持MVQ链接，用于量子计算机控制、校准、纠错和混合模拟 [2][3] - 英伟达与Uber合作，将Nvidia Drive Hyperion汽车连接到全球网络，发展无人驾驶出租车业务 [4] 超算与科研 - 美国能源部与英伟达合作，构建七个新的AI超级计算机，以推动国家科学发展 [3] 开源与美国制造 - 英伟达致力于开源，认为这对美国至关重要，特别是对初创企业 [4] - 英伟达强调美国制造业的回归 [4] 公司愿景 - 英伟达表达了对美国的自豪感和对美国在全球科技领域保持领先地位的期望 [5] - 电信是经济、产业和国家安全的支柱 [1]

Core Insights - The rise of AI and accelerated computing is viewed as a significant development, with skepticism about a potential bubble being dismissed as unfounded [2][11] - Companies like Kamico and Bloom Energy are highlighted as examples of firms that are successfully navigating the data center and clean energy markets, leading to substantial stock price increases [5][7] Company Analysis - Kamico, a uranium company, saw a 23% stock increase following a government partnership for an $80 billion nuclear buildout, driven by data center power demand [5] - Bloom Energy, which faced years of stagnation, reported a strong quarter leading to an 18% stock increase, establishing itself as a leader in clean energy solutions for data centers [7] Industry Trends - The data center buildout is creating significant investment opportunities, particularly in AI and clean energy sectors, with many companies working to innovate in power generation and data processing [2][8] - Speculative stocks are currently yielding high returns, suggesting a favorable environment for investors willing to take calculated risks [10][12]

Group 1 - The core viewpoint is that AI has reached a level of capability that justifies its cost, indicating a shift in computing models from general-purpose to accelerated computing [1][2] - The transition is not viewed as a bubble, but rather a natural evolution in technology, emphasizing the importance of scaling to meet increasing demand [1] - Companies are investing significantly in AI technologies, reflecting their satisfaction with the performance and outcomes generated by these systems [2][3] Group 2 - AI's reasoning and research capabilities have improved, leading to the generation of valuable intelligence and tokens that companies are willing to pay for [2] - Various AI models are being utilized across different applications, showcasing the diverse use cases and the willingness of companies to invest in these technologies [3]

Strategic Partnership & Technological Advancement - Nvidia and Nokia are partnering to leverage the transition from general-purpose computing to accelerated computing and AI, aiming to win back telecommunications for America [2] - The partnership focuses on building a network leveraging AI for 6G services, marking a significant change in network infrastructure [5] - Nvidia's technology, particularly the CUDA software stack, accelerates Nokia's innovation and enables faster movement in the industry [16][17] - The collaboration brings AI to radio networks (RAN) to improve wireless communication efficiency and provide AI services for robotics, autonomous vehicles, and industrial automation [7] - The partnership aims to counter competitors in markets like Europe, the Middle East, and Africa by combining Nokia's Airscale technology with Nvidia's platform [9] Market & Financial Implications - Nvidia invested in Nokia due to optimism and excitement about the potential success of their collaboration [14] - Nvidia anticipates a $500 billion market opportunity over five financial quarters, solely from the data center business [20] - The mentioned $500 billion does not include networking, Nvidia Drive Hyperion platform, ARC platform, or quantum platform [21] - AI is now considered valuable, with companies willing to pay for its reasoning and intelligence capabilities [31] Future Outlook & Deployment - Customer trials for the partnership's work are expected early next year, with full commercial production anticipated in 2027 [22][23] - The partnership accelerates the timeline for deploying new technologies, allowing for software updates to adapt to evolving standards [24][25]

Core Insights - The partnership between the companies aims to leverage American technology for national security and economic reasons, focusing on AI and accelerated computing to enhance telecommunications in the U.S. [2][3][12] Group 1: Strategic Importance - The transition from general-purpose computing to accelerated computing and AI is seen as crucial for regaining leadership in telecommunications [2][5] - The partnership with Nokia is highlighted as essential for integrating AI into radio networks, enhancing wireless communication efficiency [6][7] Group 2: Innovation and Technology - The collaboration is expected to foster innovation by combining strengths in AI and telecommunications, leading to the development of next-generation 6G technology [13][18] - The companies are focused on creating a network that supports advanced applications such as robotics, autonomous vehicles, and augmented reality [5][12] Group 3: Market Dynamics - The partnership is positioned as a response to global competition, particularly against players like Nokia and others in Europe, the Middle East, and Africa [9][10] - The companies aim to differentiate themselves by doing what they excel at while leveraging partnerships for broader capabilities [10][11] Group 4: Financial Outlook - The companies announced a significant financial projection of $500 billion over six financial quarters, indicating strong growth expectations [20][21] - The partnership is expected to accelerate timelines for product development and deployment, with customer trials anticipated early next year and full commercial production expected by 2027 [22][23][24] Group 5: AI and Computing Transition - The shift towards accelerated computing is framed as a natural evolution rather than a bubble, with AI now being recognized as a valuable asset worth investing in [31][32] - The companies are committed to innovating faster and more effectively by integrating AI into their operations and product offerings [17][31]

Core Insights - Synopsys, Inc. is showcasing advancements in engineering solutions at NVIDIA GTC, emphasizing the integration of AI and GPU-accelerated computing to enhance engineering productivity and innovation [1][2][3] Group 1: AI and GPU Integration - Synopsys is collaborating with NVIDIA to enhance AI integrations for smarter manufacturing, chip design, and physics simulation, enabling faster and more intuitive engineering processes [2][3] - The collaboration includes the integration of Synopsys AgentEngineer technology with NVIDIA's NeMo Agent Toolkit, aimed at improving autonomous design flows and accelerating time to market [4] Group 2: Performance Improvements - Ansys Fluent® fluid simulation software achieved a 500x speedup using GPU-accelerated computing, completing simulations that previously took two weeks in approximately 40 minutes [5] - Synopsys QuantumATK® atomistic simulation has shown up to a 15x improvement in time to results for density functional theory (DFT) and Non-equilibrium Green's Function (NEGF) methods, significantly enhancing materials research and semiconductor design [6] Group 3: Industry Impact - The advancements in AI and GPU-accelerated solutions are positioned to redefine engineering capabilities, enabling engineers to simulate real-world complexities with high fidelity and speed [3][4] - Northrop Grumman Microelectronics Center is utilizing Synopsys QuantumATK with NVIDIA GPUs to accelerate the development of next-generation materials, reducing development time from weeks to hours [6]

Summary of NVIDIA 2025 Conference Call Company Overview - **Company**: NVIDIA (NasdaqGS: NVDA) - **Event**: 2025 Conference - **Date**: October 28, 2025 Key Industry Insights - **Artificial Intelligence (AI)**: AI is described as the new industrial revolution, with NVIDIA's GPUs at its core, likened to essential infrastructure like electricity and the Internet [6][11][12] - **Accelerated Computing**: NVIDIA has pioneered a new computing model termed "accelerated computing," which is fundamentally different from traditional computing models. This model leverages parallel processing capabilities of GPUs to enhance computational power [11][14][15] - **Telecommunications**: A significant partnership with Nokia was announced, aiming to integrate NVIDIA's technology into the telecommunications sector, particularly for the development of 6G networks [27][30][31] Core Technological Developments - **NVIDIA ARC**: Introduction of the NVIDIA ARC (Aerial Radio Network Computer), designed to run AI processing and wireless communication simultaneously, marking a revolutionary step in telecommunications technology [28][29] - **Quantum Computing**: NVIDIA is advancing quantum computing by connecting quantum processors directly to GPU supercomputers, facilitating error correction and AI calibration [38][40][41] - **CUDA and Libraries**: The CUDA programming model and various libraries developed by NVIDIA are crucial for maximizing the capabilities of GPUs and enabling developers to create applications that utilize accelerated computing [16][21][22] Financial and Market Position - **Market Growth**: NVIDIA anticipates significant growth driven by the demand for AI and accelerated computing, with projections indicating visibility into half a trillion dollars of cumulative revenue through 2026 [108] - **Investment in Infrastructure**: Major cloud service providers (CSPs) are expected to invest heavily in capital expenditures (CapEx) to adopt NVIDIA's advanced computing technologies, enhancing their operational efficiency [103] Additional Insights - **AI's Role in the Economy**: AI is positioned as a transformative force that will engage previously untapped segments of the economy, potentially addressing labor shortages and enhancing productivity across various industries [63] - **Technological Shifts**: The industry is experiencing a shift from general-purpose computing to accelerated computing, with NVIDIA's GPUs being uniquely capable of handling both traditional and AI workloads [106] Conclusion NVIDIA is at the forefront of several technological revolutions, particularly in AI and accelerated computing, with strategic partnerships and innovative products that position the company for substantial growth in the coming years. The emphasis on collaboration with major players in telecommunications and the advancement of quantum computing further solidifies NVIDIA's role as a leader in the tech industry.