Financial Data and Key Metrics Changes - Revenue grew 26% year-on-year to a record $1.24 billion, marking the fourth consecutive billion-dollar quarter [5][13] - Royalties increased 27% to a record $737 million, driven by strength in AI and general-purpose data centers [5][13] - Non-GAAP EPS reached $0.43, supported by higher revenue and slightly lower operating expenses than expected [16] Business Line Data and Key Metrics Changes - License revenue was $505 million, up 25% year-on-year, driven by demand for next-generation technologies [5][14] - Data center royalty revenue has grown more than 100% year-on-year, with expectations for it to become the largest business segment in the future [5][13] - Edge AI devices, particularly smartphones, are experiencing faster growth than the market, with all major Android OEMs ramping up production of CSS-based chips [13][14] Market Data and Key Metrics Changes - Arm's share among top hyperscalers is expected to reach 50%, with significant deployments of Neoverse CPUs [8][9] - The automotive market in Physical AI grew double digits year-on-year, contributing to strong royalty performance [14] - The shift towards agent-based AI is reshaping data center design, requiring CPUs with higher core counts and better power efficiency [8][10] Company Strategy and Development Direction - Arm has organized its business around three units: Edge AI, Physical AI, and Cloud AI, to align with customer deployment of AI [6] - The company is focused on investing in innovation across a broad spectrum of compute technologies, including next-generation architectures and compute subsystems [5][16] - Arm aims to be the compute platform of choice for all AI workloads, leveraging its strengths in power efficiency and predictable latency [10][91] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in future revenue growth due to strong customer demand and a growing base of long-duration contracts at higher royalty rates [17] - The company anticipates revenue of $1.47 billion for Q4, representing an 18% year-on-year growth at the midpoint [17] - Management acknowledged potential risks from memory supply chain constraints but indicated that growth in Cloud AI is compensating for these risks [24][25] Other Important Information - Arm is hosting an event on March 24th, with no details provided ahead of the event [18] - The company is exploring chiplets and complete SoCs as part of its R&D investments [16] Q&A Session Summary Question: Arm's role in AI and cloud data centers - Management highlighted the shift from training to inference workloads, emphasizing the suitability of CPUs for agentic AI tasks due to their power efficiency and low latency [21][22] Question: Impact of memory supply chain constraints on royalty revenue - Management indicated that a potential 20% reduction in smartphone unit volumes could translate to a 1-2% negative impact on total royalties, with Cloud AI growth offsetting risks [23][24][25] Question: SoftBank's potential need to sell Arm stock - Management confirmed that SoftBank's leadership is not interested in selling any shares of Arm stock, expressing long-term confidence in the company [30] Question: Trends in royalty revenue growth - Management noted that royalty growth percentages may be lower due to tougher comparisons from previous quarters, but absolute dollar growth is expected to remain strong [31][32] Question: Data center revenue quantification - Management indicated that data center revenue is expected to grow significantly, potentially reaching similar or larger levels than the smartphone business in the coming years [39] Question: Impact of higher royalty rates on smartphone unit volumes - Management explained that the transition to higher royalty rates with v9 and CSS will help offset lower smartphone unit volumes [42][43] Question: Partnerships and custom ASICs with SoftBank - Management did not provide specific details on potential custom ASICs but acknowledged the substantial partnership with SoftBank [46] Question: Arm's IP penetration in AI data center semis - Management discussed the evolving architecture of data center chips and the increasing role of CPUs in handling AI workloads [49][50] Question: Compute subsystems' contribution to royalty revenue - Management indicated that CSS has grown from approaching double digits to well into the teens percentage of royalty revenue, with expectations for further growth [56][57]

Core Insights - The article discusses the transformative impact of AI on various industries, highlighting the advancements presented by NVIDIA at CES 2026, particularly focusing on the new Rubin platform and the Alpamayo open-source model for autonomous driving [1][3][5]. Group 1: NVIDIA Rubin Platform - The NVIDIA Rubin platform introduces six new chips aimed at creating a leading AI supercomputer that excels in cost, performance, and security, significantly reducing training time and inference token costs [8][10]. - The platform features innovations such as the latest NVIDIA NVLink interconnect technology, a Transformer engine, and advanced security measures, which collectively enhance AI capabilities and reduce the GPU count needed for training models by four times compared to previous generations [13][17]. - The Rubin platform is designed to meet the increasing demand for AI computing, with a total bandwidth of 260TB/s, surpassing the entire internet's bandwidth, and is expected to be commercially available in the second half of 2026 [19][20]. Group 2: Alpamayo Open-Source Model - The Alpamayo series introduces a visual-language-action (VLA) model that enhances autonomous driving capabilities by enabling vehicles to reason through rare scenarios, thereby improving safety and interpretability [27][28]. - This model is part of a cohesive open ecosystem that includes open-source models, simulation tools, and datasets, allowing developers to build upon it for autonomous driving technology [29][30]. - The Alpamayo model, featuring 10 billion parameters, is designed to generate driving trajectories and reasoning traces from video inputs, providing a foundation for developers to create tailored autonomous driving solutions [30][31]. Group 3: Robotics and Physical AI - NVIDIA has launched new open-source models and frameworks for physical AI, aimed at accelerating the development of versatile robots capable of learning multiple tasks [35][36]. - The company emphasizes the importance of simulation and evaluation frameworks, such as the Isaac Lab-Arena, to streamline the development process and ensure robust performance before deployment [43][45]. - Collaborations with industry leaders in robotics are highlighted, showcasing the integration of NVIDIA's technology into next-generation robots, which are expected to revolutionize various sectors [36][50].

Core Insights - Supermicro is expanding its manufacturing capacity and liquid-cooling capabilities in collaboration with NVIDIA to deliver data center-scale solutions optimized for the NVIDIA Vera Rubin and Rubin platforms [1][2] - The company’s Data Center Building Block Solutions (DCBBS) approach allows for streamlined production and faster deployment, providing a competitive edge in next-generation AI infrastructure [1][7] Manufacturing and Technology Expansion - Supermicro's partnership with NVIDIA enables rapid deployment of advanced AI platforms, enhancing speed, efficiency, and reliability for hyperscalers and enterprises [2] - The company is investing in expanded manufacturing facilities and a comprehensive liquid-cooling technology stack to streamline production and deployment of fully liquid-cooled NVIDIA platforms [7] Product Features - The NVIDIA Vera Rubin NVL72 SuperCluster integrates 72 NVIDIA Rubin GPUs and 36 NVIDIA Vera CPUs, delivering 3.6 exaflops NVFP4 performance and 1.4 PB/s HBM4 bandwidth [5] - The 2U Liquid-cooled NVIDIA HGX Rubin NVL8 Systems provide 400 petaflops NVFP4 and 176 TB/s HBM4 bandwidth, optimized for AI and HPC workloads [5] - The platform features NVIDIA NVLink 6 for high-speed interconnects, NVIDIA Vera CPU with 2x performance over the previous generation, and advanced reliability features [5][6] Networking and Storage Solutions - The NVIDIA Vera Rubin platform includes NVIDIA Spectrum-X Ethernet Photonics networking, offering 5x power efficiency and 10x reliability compared to traditional optics [6] - Supermicro's storage solutions support the NVIDIA BlueField-4 DPU, enhancing data management capabilities [6] Strategic Positioning - Supermicro's modular DCBBS architecture accelerates deployment and time-to-online, ensuring customers achieve first-to-market advantages [7] - The company is committed to delivering innovative IT solutions across various sectors, including AI, cloud, and 5G infrastructure [8]

Core Insights - NVIDIA launched the Rubin platform, featuring six new chips aimed at creating a powerful AI supercomputer that sets a new standard for AI system deployment and security at lower costs, facilitating mainstream AI adoption [2][4] - The platform utilizes extreme codesign across its components, which include the NVIDIA Vera CPU and NVIDIA Rubin GPU, to significantly reduce training time and inference costs [3][5] Innovations and Features - Rubin introduces five key innovations: advanced NVLink interconnect technology, Transformer Engine, Confidential Computing, RAS Engine, and the NVIDIA Vera CPU, enabling up to 10x lower inference costs and 4x fewer GPUs for training compared to the previous Blackwell platform [5][10] - The platform supports massive-scale mixture-of-experts (MoE) model inference, enhancing AI capabilities while reducing operational costs [5][10] Ecosystem and Partnerships - Major AI labs and cloud service providers, including AWS, Google, Microsoft, and OpenAI, are expected to adopt the Rubin platform, indicating broad ecosystem support [6][26] - Collaborations with companies like CoreWeave, Dell, and HPE aim to integrate Rubin into their AI infrastructures, enhancing performance and scalability [9][25] Performance and Efficiency - The Rubin platform is engineered to deliver exceptional performance, with the NVIDIA Vera Rubin NVL72 rack providing 260TB/s bandwidth, surpassing the entire internet's capacity [10][20] - Advanced Ethernet networking through Spectrum-6 technology enhances data center efficiency, achieving 5x better power efficiency and reliability compared to traditional methods [19][18] Market Readiness - The Rubin platform is in full production, with products expected to be available from partners in the second half of 2026, marking a significant step in AI infrastructure evolution [22][24] - Companies like Microsoft and AWS are set to deploy Rubin-based instances, further solidifying its role in next-generation AI capabilities [23][22]