Investment Rating - The report assigns a "Buy" rating for NVIDIA (NVDA US) with a target price of $168.00, indicating a potential upside of 45.5% from the current price of $115.43 [1][12]. Core Insights - The report highlights NVIDIA's transition towards generative AI, with CEO Jensen Huang predicting that capital expenditures in the cloud service provider (CSP) sector could exceed $300 billion by 2025 and reach $1 trillion by 2028 [2]. - NVIDIA is actively participating in AI transformations across vertical industries, including mobile communications and smart driving, with a vision of establishing "AI factories" for production planning and intelligent assistance [2]. - The company continues to release new products, with significant upgrades in data center offerings, emphasizing the importance of scale-up architecture over scale-out in server design [6]. Financial Overview - Revenue projections for NVIDIA show substantial growth, with expected revenues of $60,922 million in 2024, increasing to $311,585 million by 2028, reflecting a compound annual growth rate (CAGR) of 15.2% [5][14]. - Net profit is forecasted to rise from $32,312 million in 2024 to $180,404 million in 2028, with a notable increase in earnings per share (EPS) from $1.30 to $7.30 over the same period [5][14]. - The report indicates a significant improvement in profit margins, with gross margins expected to remain around 75% and net margins projected to increase to 57.9% by 2028 [16]. Product Development and Roadmap - NVIDIA's product roadmap includes the launch of the Blackwell Ultra chip in the second half of 2025, followed by the Rubin and Rubin Ultra chips in 2026 and 2027, respectively, showcasing substantial performance upgrades [6][7]. - The introduction of new switch products, Spectrum-X and Quantum-X, is planned for 2025 and 2026, respectively, with advancements in technology such as optical-electrical hybrid packaging [8]. Market Position and Valuation - NVIDIA's current price-to-earnings (P/E) ratio is noted at 24 times the FY26 earnings, which is considered attractive compared to its historical average of 38 times [6]. - The report emphasizes NVIDIA's strong product and technology advantages, particularly in the early stages of AI deployment both domestically and internationally [6].

Core Viewpoint - NVIDIA's recent GTC conference showcased the launch of its new generation of AI chips, emphasizing the importance of inference efficiency over sheer computational power, with DeepSeek emerging as a significant player in this landscape [2][4][6]. Group 1: AI Chip Developments - NVIDIA introduced the Blackwell Ultra chip, which is set to deliver 20 petaflops of AI performance and features 288GB of HBM3e memory, marking a significant upgrade from its predecessor [10][12]. - The Blackwell Ultra chip will support various AI tasks, including pre-training, post-training, and inference, making it a versatile platform [10][12]. - The upcoming Rubin chip, expected in late 2026, will offer performance improvements of up to 900 times compared to the Hopper architecture, with capabilities reaching 3.6 ExaFLOPS for inference tasks [19][20][23]. Group 2: Inference Efficiency - The conference highlighted that the future of AI competition will hinge on achieving the lowest inference costs and highest efficiency, rather than merely increasing model size [6][4]. - NVIDIA's DeepSeek-R1 model achieved a throughput of over 30,000 tokens per second, showcasing a 36-fold increase in throughput since January [49][50]. - The company aims to optimize its entire inference ecosystem, integrating advanced tools to enhance performance across various frameworks [50][58]. Group 3: Networking Infrastructure - NVIDIA introduced the Spectrum-X and Quantum-X silicon photonic switches to enhance AI factory connectivity, significantly reducing energy consumption and operational costs [30][32]. - The new networking technology is designed to support millions of GPUs across sites, addressing the growing demand for bandwidth and low latency in AI applications [29][34]. Group 4: AI Factory Concept - NVIDIA's vision for the future includes the concept of AI factories, where every industry will operate both a physical factory and an AI factory, with Dynamo serving as the operating system for these AI environments [36][35]. - The company is positioning itself as a leader in transforming GPU computing into a foundational infrastructure for various industries, moving beyond traditional chip manufacturing [54][58]. Group 5: Robotics and AI Integration - The conference featured the introduction of the Isaac GR00T N1, a humanoid robot model that utilizes advanced AI frameworks for real-world applications [41][43]. - NVIDIA's collaboration with Google DeepMind and Disney Research on the open-source physics engine Newton aims to enhance robotic capabilities and AI learning [45][46].