2025上半年AI核心成果及趋势报告 量子位智库 2025-7_01

Application Trends - General-purpose agents are deeply integrating tools to complete diverse research tasks, with a focus on visual operations through Computer Use Agents (CUA) [1][6][11] - Vertical application scenarios are beginning to adopt agentification, with natural language control becoming part of vertical workflows [11][12] - AI programming is emerging as a critical competitive area, with both domestic and international players intensively laying out their strategies [2][13] Model Trends - The model inference capabilities are continuously improving, particularly in mathematical and coding domains, with large models transitioning towards agentic functionalities [1][18][19] - The Model Context Protocol (MCP) is accelerating the application of large models, enabling them to access extensive external information and control existing software applications [15][16] - The performance of models in reasoning tasks is significantly enhanced, with the ability to handle complex tasks through integrated tool usage [19][28] Technical Trends - Training resources are increasingly shifting towards post-training and reinforcement learning, while pre-training still has ample room for optimization [29][30] - The Transformer architecture is rapidly iterating, with optimizations focusing on attention mechanisms and neural network layers [35][36] - Multi-agent systems are emerging as a new paradigm, enhancing efficiency and robustness in dynamic environments [31][32] Industry Trends - xAI's Grok 4 has entered the global large model first tier, altering the competitive landscape of model layers [2] - Computational power is becoming a key competitive factor, with leading players continuously expanding their computing clusters [2][12] - The gap between Chinese and American general-purpose large models is narrowing, with China excelling in multi-modal fields [2][12]