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实探|今日看点,上海这场会AI含量拉满、机器人成分爆表!
证券时报· 2025-07-26 15:33
Core Insights - The 2025 World Artificial Intelligence Conference opened with the theme "Intelligent Era, Common Ball" showcasing various AI applications and innovations in robotics and education technology [1][3][5]. Group 1: AI Innovations and Applications - The conference featured robots as central figures in various settings, including convenience stores and manufacturing workshops, highlighting the integration of AI in everyday tasks [1]. - NetEase Youdao presented the world's first virtual language tutor, allowing users to interact in English, demonstrating advancements in AI-driven educational tools [3]. - Youdao's AI answering pen, SpaceOne, aims to address traditional learning limitations by providing real-time AI assistance for complex subjects, showcasing a significant technological breakthrough in multi-modal visual processing [5]. Group 2: AI Infrastructure and Solutions - Wu Wenxin's AI solutions were introduced, including three major products: "Wu Qiong AI Cloud," "Wu Jie Intelligent Computing Platform," and "Wu Yin Terminal Intelligence," designed to support diverse AI applications across various scenarios [5][6]. - The CEO of Wu Wenxin emphasized the need for scalable AI infrastructure to meet the demands of small and diverse AI application enterprises, likening it to building a "giant power plant" for AI capabilities [6]. Group 3: Hardware Developments - Zhonghao Xinying showcased its self-developed high-performance TPU AI chip "Shan Na" and AI server "Tai Ze," which offers superior performance and energy efficiency, with energy consumption at only 70% of traditional GPUs [8]. - The server's design allows for easy deployment and maintenance, indicating a shift towards more efficient AI hardware solutions [8]. Group 4: Industry Trends and Insights - Inspur Group highlighted the rapid integration of AI across industries, transitioning from "AI available" to "AI economically feasible," which is crucial for digital transformation [10]. - Key factors for AI implementation include the need for a combination of discriminative and generative AI capabilities, data governance, and the establishment of a robust digital foundation for enterprises [10].