Core Insights - The upcoming GTC 2026 conference hosted by NVIDIA is not just about showcasing new GPUs but aims to redefine the rules of AI infrastructure [9][3] - The market is focused on whether NVIDIA can transition from a hardware company to a platform company that defines AI infrastructure [3][8] - The conference will likely influence the valuation of NVIDIA and the entire AI industry chain, potentially leading to significant shifts in investment focus [8][9] Group 1: Key Themes of GTC 2026 - The core message of GTC is to redefine the game rules of AI infrastructure rather than just showcasing new products [9] - The focus is shifting from single-chip performance to system-level optimization, emphasizing collaboration among chips, networks, memory, and software [10][11] - The concept of workload decomposition is crucial, indicating that AI tasks will require specialized resources rather than relying on a single powerful GPU [12][15] Group 2: System-Level Dominance - NVIDIA's strategy is to enhance its system-level dominance by optimizing the allocation of resources for different AI tasks [15][17] - The importance of network and interconnect technology is highlighted, as they will determine the efficiency of AI systems in a multi-chip environment [18][19] - The investment focus is shifting from GPU performance to the underlying network infrastructure, which is essential for data transfer speed and latency [19][20] Group 3: Memory Technology and Tokenomics - NVIDIA is introducing SRAM for low-latency inference while maintaining HBM for large-scale training, indicating a complementary approach rather than a replacement [24][28] - The focus on tokenomics is crucial, as it addresses the cost-effectiveness of AI infrastructure and the return on investment for new technologies [30][32] - The expected EPS for NVIDIA in FY2028 is projected to reach $15, suggesting a low forward P/E ratio of 12, indicating significant market undervaluation [32] Group 4: Future Product Roadmap - The next-generation products from NVIDIA, such as Blackwell and Rubin, are not just about stronger GPUs but represent a strategic shift towards system-level capabilities [34][36] - The emphasis will be on how many computations, bandwidth, and memory can be accommodated in a single rack, along with managing power consumption and interconnects [36] - NVIDIA's goal is to push for infrastructure standardization and systemization, moving from merely selling chips to offering a unique AI system [36]