2026年，AI将从炒作走向务实

Core Insights - 2026 is anticipated to be a pivotal year for AI, transitioning from large-scale model development to practical applications that integrate AI into real-world workflows [2][34] - The focus is shifting towards deploying lightweight models and embedding intelligence into physical devices, moving away from mere demonstrations to targeted deployments [2][34] Group 1: Scaling Law and Model Development - The AI industry is nearing the limits of the Scaling Law, prompting a shift towards new architectural research and smaller, more efficient models [4][21] - Experts suggest that smaller language models (SLMs) will become the standard in AI applications by 2026 due to their cost-effectiveness and performance advantages [5][22] - The trend towards SLMs is supported by advancements in edge computing, making them more suitable for deployment on local devices [6][22] Group 2: World Models and Gaming Industry - 2026 is expected to be a key year for world models, which learn how objects interact in three-dimensional space, enhancing predictive capabilities [8][25] - The gaming industry is projected to see significant growth in the world model market, with estimates rising from $1.2 billion in 2022 to $27.6 billion by 2030 [9][25] Group 3: Agent Integration and Practical Applications - The introduction of the Model Context Protocol (MCP) is seen as a critical advancement, enabling AI agents to interact with external tools and databases, thus facilitating their integration into real-world systems [11][27] - As MCP reduces friction in connecting AI agents to practical systems, 2026 may mark the year when these agents transition from demonstration to everyday use [12][28] Group 4: Human-AI Collaboration - There is a growing belief that AI will enhance human workflows rather than replace them, with expectations of new job roles emerging in AI governance and data management [14][31] - The narrative is shifting towards how AI can assist human tasks, with predictions of a low unemployment rate as companies begin to hire for new roles related to AI [14][31] Group 5: Physical AI and Market Trends - Advances in small models, world models, and edge computing are expected to drive the adoption of physical AI applications, including robotics and wearable devices [16][34] - The market for physical AI is anticipated to grow, with wearable devices becoming a cost-effective entry point for consumers [17][34]