直击科博会：从“+AI”到“AI+” 大模型重构产业格局

Group 1 - The 27th China Beijing International Science and Technology Industry Expo showcased over 800 technology companies and institutions, featuring more than 600 globally debuting and industry-first technological achievements [1] - AI technology is rapidly transforming industry dynamics, shifting from a "+AI" integration model to an "AI+" scenario-driven model, significantly reshaping production and lifestyle [1] - The "Beijing Action Plan for Promoting 'Artificial Intelligence+'" focuses on the precise implementation of "large models + vertical scenarios," driving the digital and intelligent transformation of enterprises [1] Group 2 - Companies are advised to anchor their strategies on "high-value scenario exploration and data asset accumulation," utilizing standardized solutions for general business scenarios and customized development tools for specific scenarios [2] - The education technology sector is witnessing innovation, with products like the AI answering pen from NetEase Youdao providing immersive learning experiences through deep reasoning engines [2] - The financial technology sector is also seeing deep AI penetration, with institutions showcasing applications of large models in credit risk control, wealth management, and intelligent investment research [2] Group 3 - General large models possess strong knowledge generalization and language understanding capabilities but have high resource consumption and training costs, while vertical models focus on specialized knowledge and offer better business adaptability [3] - The mainstream industry path is a collaborative architecture of "general models + industry-specific models," enhancing practical application effectiveness [3] - In the financial sector, vertical large models may become the main battlefield for differentiated competition, with data quality and specialized knowledge bases being core barriers [3] Group 4 - Several technology companies showcased collaborative innovation results in building an open-source ecosystem for AI, which significantly promotes technological innovation and knowledge sharing [4] - The open-source ecosystem enhances the accessibility of AI technology, allowing companies to invest more economically and flexibly in acquiring and deploying AI solutions [4] - Companies can focus on application selection and data and knowledge mining, generating more commercially valuable AI applications [4]