HTSC·2025-06-10 01:43Group 1: Global AI Outlook - The report highlights a new paradigm in AI development characterized by new scaling, new architecture, and new total addressable market (TAM) opportunities [1] - The demand for computing power is expected to rise due to advancements in both training and inference processes, potentially unlocking new TAMs [1][3] - The report maintains a positive outlook on AI industry investments, anticipating that global AI applications will enter a performance harvesting phase [1] Group 2: Model Development - The pre-training scaling law is anticipated to open a new starting point for model development, with significant innovations in architecture being explored [2][23] - The report notes that the classic transformer architecture has reached a parameter scale bottleneck, with existing public data nearly exhausted [2][20] - Major tech companies are experimenting with new architectures, such as Tencent's Hunyuan TurboS and Google's Gemini Diffusion, which may accelerate scaling law advancements [23][24] Group 3: Computing Power Demand - The report identifies a clear long-term upward trend in computing power demand, driven by both training and inference needs [3][32] - New scaling paths are emerging in the post-training phase, with ongoing exploration of new architectures that may reignite pre-training demand narratives [3][33] - The deployment of large-scale computing clusters, such as OpenAI's StarGate, is expected to support the exploration of pre-training [38] Group 4: Application Development - The report indicates that the rapid advancement of agent applications is leading to a performance harvesting phase for global AI applications [4][67] - The commercialization of agent products is accelerating, with domestic AI applications quickly iterating and entering the market [4][67] - The report emphasizes that agent applications are evolving from simple tools to complex solutions, with significant growth expected in various sectors [5][68] Group 5: Business Model Transformation - The shift from traditional software delivery to outcome-based delivery is highlighted as a key trend, with quantifiable ROI accelerating the adoption of agent applications [5] - Specific sectors such as consumer-facing scenarios (advertising, e-commerce) and AI in marketing/sales are expected to lead in commercialization due to their inherent advantages [5][67] - The report notes that AI applications in HR are transitioning from efficiency tools to strategic hubs, indicating a broader transformation in business models [5][67]