Preface: Brain-Inspired AI Research

被引:0
|
作者
GONG YiHong [1 ]
WANG GuoYin [2 ,3 ,4 ]
机构
[1] College of Artificial Intelligence, Xi'an Jiaotong University
[2] Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications
[3] Key Laboratory of Cyberspace Big Data Intelligent Security, Chongqing University of Posts and Telecommunications
[4] College of Computer and Information Science, Chongqing Normal
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
<正>Large AGI (artificial general intelligence) models, represented by OpenAI’s GPT-4, DALL-E, Sora, etc., have amazed the world by exhibiting superior capabilities on a variety of NLP and text-to-image/video generation tasks. The success of these models was achieved by exploiting ultra-scale training data, ultra-scale computational models, and unlimited computing power.This brute force approach, however, is not only making an adverse impact on global warming prevention, but also raising skepticism on whether such a development path can really achieve true AGI systems. Recently, there have been increasing scientific studies that report the delusion phenomenon of the AGI models, mainly caused by their inability to learn correct knowledge and correct world models.
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