第一是场景的极端性与碎片化，如地下500米的矿井充斥粉尘、潮湿与信号屏蔽；精密面板产线上可能 存在上百种微米级缺陷，通用模型难以直接应对这些极端、离散的现场环境。 "AI重在应用，不重在发明。发明AI只是一家IT公司，应用AI则会强大一个国家。" 近日，任正非在ICPC上没有谈大模型的参数竞赛，也没有谈技术巨头的军备比拼，而是将话题引向了 高炉、矿井和码头这些实体经济的核心场景。 他的判断引发了行业的广泛共鸣，也让一个共识逐渐浮现：AI的下半场，不在于模型本身有多强大， 而在于它能在多大程度上与真实世界的复杂场景相结合。 1.技术的价值在于落地 技术史反复印证了一个规律：一项颠覆性技术的价值，最终由其应用场景所定义。多年前，施乐率先发 明了图形界面和鼠标，但这些足以改变世界的技术却被锁在实验室；直到乔布斯将它们嵌入个人电脑， 才真正开启了一个时代。 今天的AI正处于一个类似的十字路口。顶尖科技巨头们纷纷构建更强大的通用大模型，他们将此视为 类似"发电厂"的基础设施。然而，对工业制造、能源开采、交通物流等具体产业场景而言，它们需要的 远不止是"点亮一盏灯泡"那么简单。 发电厂发出的电，须经过一整套由变压器、输电 ...

Core Viewpoint - The article emphasizes the transition of generative AI from a flashy technology to a practical tool that delivers real business value, highlighting the importance of "landing" AI applications in real-world scenarios [3][6][10]. Group 1: Current State of Generative AI - Over the past two years, the excitement around generative AI has led to numerous ambitious projects, but many have failed to deliver tangible results, remaining in the demo stage [3][4]. - The disconnect between technology and real business applications has resulted in many AI solutions being perceived as "toys" rather than valuable tools [3][4]. Group 2: Successful Applications of AI - There are notable examples where AI has successfully improved industrial processes, such as enhancing product quality in manufacturing and increasing conversion rates in marketing through personalized content generation [5][6]. - AI is also transforming enterprise operations by streamlining complex processes and freeing employees from repetitive tasks, allowing them to focus on more creative work [5][6]. Group 3: The Importance of "Landing" AI - The concept of "landing" AI is crucial as it directly relates to real investment returns, efficiency improvements, and cost reductions [10]. - Successful AI applications can lead to enhanced user experiences and employee creativity, while poor implementations complicate processes and confuse users [10]. Group 4: The "Big Whale List" Initiative - The "Big Whale List" aims to identify companies that effectively implement AI in two key areas: smart manufacturing and enterprise operations [7][8]. - The initiative seeks to recognize companies that are willing to experiment and iterate in real-world scenarios, thereby growing into significant players in their industries [7][8]. Group 5: Benefits of Participation - Being part of the "Big Whale List" offers companies not only recognition but also opportunities for accelerated growth through industry validation and connections with decision-makers [9][11]. - The list serves as a platform for showcasing successful AI applications, transforming them into industry benchmarks [11][12]. Group 6: Evaluation Mechanism - The evaluation process for the "Big Whale List" focuses on real value and landing results, avoiding superficial concepts and ensuring a rigorous assessment by experts from various fields [12]. - The initiative aims to create value connections through case studies, media exposure, and high-level networking opportunities [12]. Group 7: Future Outlook - As generative AI evolves, the focus will shift from flashy presentations to the practical efforts of companies that are deeply engaged in industry applications [13]. - Companies with verifiable and replicable AI solutions are encouraged to participate in this movement towards a value-driven AI era [13].