Emergence of machine language: towards symbolic intelligence with neural networks

作     者：Yuqi Wang Xu-Yao Zhang Cheng-Lin Liu Tieniu Tan Zhaoxiang Zhang Yuqi Wang;Xu-Yao Zhang;Cheng-Lin Liu;Tieniu Tan;Zhaoxiang Zhang

作者机构：State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences 

出 版 物：《National Science Review》 (国家科学评论(英文版))

年 卷 期：2024年第11卷第4期

页      面：27-30页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the 2035 Innovation Program of CAS the National Key R&D Program of China (2022ZD0160102) the National Natural Science Foundation of China (61836014,U21B2042, 62072457 and 62006231) 

主　　题：intelligence emergence language with machine networks neural symbolic towards 

摘      要：Representation learning is a core issue in artificial intelligence (AI). Currently,there exists a disparity in the choice of representation between humans and machines. Humans rely on discrete language for communication and learning, whereas machines utilize continuous features for computation and representation.