对话黑湖科技周宇翔：AI很好解决了能力泛化的问题，我们正在加速推进AI在工业场景的落地应用

Core Viewpoint - The application of AI in industrial scenarios is not industry-specific but rather scene-specific, redefining the human-machine relationship and emphasizing the importance of product and engineering innovation to mitigate issues like "hallucinations" in AI models [1][2]. Group 1: AI in Industrial Applications - AI's role is to automate tasks previously performed by humans, with software remaining the core medium, but the interaction and execution methods are evolving [1]. - The challenge lies in balancing the hallucinations of AI models with the precision required in industrial settings, necessitating reliable control strategies and feedback mechanisms in application design [1][2]. Group 2: Architectural Innovations - Black Lake Technology has developed an intermediate layer architecture that is auditable and deterministic, addressing the rigidity of previous systems that relied heavily on manual configuration [2]. - This new architecture significantly reduces deployment and maintenance costs in complex factory environments, enhancing flexibility [2]. Group 3: Scene-Based AI Logic - AI's application logic should focus on common production scenarios, such as defect detection and task scheduling, rather than being confined to specific industries [2]. - The ability of AI to generalize across different scenes allows for a unified solution to common problems faced by various industries, contrasting with traditional systems that required costly, customized solutions [2]. Group 4: Integration of AI and Software - The true value of AI lies in its ability to transform the traditional human-operated software model, enabling automation and adaptability in data and decision flows [3]. - Black Lake Technology has shifted from using cloud computing to integrating AI capabilities from various platforms, including Huawei, to enhance their software offerings, reflecting a rapid evolution in the industry [3].