大模型在工业领域落地有难有易

Core Insights - The consensus in the industry is that AI large models are set to reconstruct and upgrade various sectors, with significant advancements observed in 2023 [1] - Major cloud service providers in China, such as Tencent Cloud, Volcano Engine, and Baidu Smart Cloud, have reported the deployment of large models across multiple fields, particularly in consumer hardware integration [1][2] - The application of large models in industrial manufacturing is still emerging, with collaborations primarily focused on smart cockpit interactions and marketing strategy optimization, while core manufacturing processes remain underexplored [1] Application Areas - The most widespread applications of large models are in internal knowledge management and building AI knowledge bases, particularly in knowledge-intensive industries [2] - Companies like China Chemical Wuhuan are actively developing AI knowledge bases to consolidate the expertise of their highly educated engineers, enhancing operational efficiency [2] - In the industrial sector, low-risk scenarios such as marketing services and customer service are seeing faster adoption of large models due to their higher tolerance for errors [3] Challenges in Implementation - The integration of large models into core manufacturing processes faces significant challenges, particularly due to the low tolerance for errors in production control and safety operations [5][6] - Current AI applications in production processes are limited, with companies hesitant to rely on large language models for critical decision-making due to their black-box nature and low interpretability [5][6] - The return on investment (ROI) for AI quality inspection solutions has not significantly surpassed traditional methods, leading to cautious exploration of AI applications in manufacturing [6]