和讯·2025-11-21 10:15Core Viewpoint - The rapid advancement of generative AI and large models contrasts with the slow commercial adoption, as evidenced by a recent decline in the percentage of U.S. companies using paid AI products [2][3]. Group 1: AI Project Challenges - Approximately 90% of vertical enterprises do not truly understand AI, leading to ineffective implementation without tailored models [3]. - The telecom industry has historically absorbed new technologies, and AI is seen as the next evolution, with significant advancements expected by 2025 [3]. Group 2: Future of AI and Agent Technology - The AI industry is at a crossroads, with a shift from foundational model development to large-scale application deployment, raising questions about the future of basic model research [6]. - There is a consensus that future AGI will rely on world models that integrate multiple modalities, although specific applications may require tailored models for efficiency [6][7]. - The development of specialized models for various industries is viewed as a practical approach to achieving commercial viability before moving towards universal models [7]. Group 3: Agent Technology Implementation - By 2025, agent technology is expected to become a core trend, with practical applications emerging across various industries, including healthcare and education [8]. - Current implementations of agent technology have demonstrated effectiveness, with plans for broader deployment in 2026 [8]. - Challenges remain in integrating agents into existing workflows, primarily due to limitations in multi-modal capabilities of large models [8][9]. Group 4: Computational Power and Industry Growth - The AI industry faces ongoing challenges related to computational power, with domestic GPU companies accelerating their development to address these needs [9]. - As computational issues are resolved, significant advancements in multi-modal models and agent technology are anticipated [9][10]. Group 5: Consumer Acceptance and Market Trends - Consumer acceptance of AI products is increasing, with a shift towards deploying AI capabilities from cloud to edge devices [9][10]. - The mobile AI sector is expected to see rapid growth, with small models achieving high accuracy in practical applications [11]. Group 6: Humanoid Robots and Industry Development - Humanoid robots are still in the exploratory phase, with significant technical challenges remaining before widespread commercial deployment [12][13]. - The manufacturing of humanoid robots involves complex components, with a focus on developing autonomous control capabilities as a critical bottleneck [13]. - The path to commercial viability for humanoid robots is expected to begin in industrial settings before expanding to consumer applications [14][15].