豆包手机后思考：AGI会在中国率先跑出来吗？

Core Insights - The article discusses the rapid advancement of AI technology in the Chinese market, particularly focusing on the launch of the Nubia M153, which integrates AI assistants with system-level execution capabilities, allowing AI to perform tasks autonomously rather than just providing suggestions [1][2][3] - The emergence of AI agents signifies a shift from AI being merely a thinking entity to one that can take action, raising questions about the readiness of existing digital ecosystems to accommodate such capabilities [2][3][4] - The Chinese market is positioned as a unique testing ground for AI agents due to its high application density, user acceptance, and a more unified governance system, potentially allowing it to lead in this technological transformation [3][18][23] AI Value Consensus: Transition from "Thinking" to "Action" - "Thinking" AI is reaching a ceiling, as evidenced by OpenAI's financial struggles, where costs are outpacing revenue significantly [4][6] - The cost structure of AI models is becoming unsustainable, with increasing computational demands not matched by revenue growth, indicating a need for AI to evolve towards actionable capabilities [6][7] - The focus is shifting towards AI's ability to act, as the next value point lies in its capacity to execute tasks rather than just process information [6][7] The Role of Mobile Devices in AI Action - Mobile devices are central to the AI action landscape, with Chinese users averaging 6.2 hours of smartphone use daily, performing over 120 digital actions [8] - The operating systems of mobile devices inherently possess the necessary permissions and infrastructure for AI to execute actions, making them ideal platforms for testing AI's commercial value [8][11] Competition for AI Execution Rights - Three main players are vying for control over AI execution capabilities: model service providers (e.g., Alibaba, Baidu, Tencent), terminal manufacturers (e.g., OPPO, Xiaomi), and native AI companies like Doubao [9][10][12] - Model service providers leverage their existing application ecosystems to integrate AI capabilities, while terminal manufacturers focus on system-level integration to expand AI's operational scope [10][11] - Native AI companies are taking a more aggressive approach by directly targeting system-level action entry points, although they face significant resistance from existing application ecosystems [12][13] Structural Challenges and Industry Transformation - The introduction of AI agents raises fundamental questions about operational permissions, commercial models, and accountability mechanisms, as traditional frameworks may not apply [14][15] - The current digital ecosystem is primarily designed for human users, which poses challenges for AI's operational integration, highlighting a need for infrastructure that supports AI actions [14][15] - As various stakeholders begin to adapt to the need for AI to operate autonomously, the industry is undergoing a structural transformation that could redefine value distribution and operational frameworks [17][18] China's Market as a Testing Ground for AI Agents - The rapid evolution of AI models and their capabilities is creating a competitive landscape, with significant advancements in model performance observed in recent years [21][22] - China's market conditions, including high service density and user acceptance of automation, provide a conducive environment for AI agents to thrive, contrasting with more fragmented markets like the U.S. [22][23] - The successful implementation of AI agents in China could lead to the development of a new operational system for AI that could be scaled globally, moving beyond mere model parameters to a comprehensive framework for AI action [23][24]