One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
Chaoning Zhang, Chenshuang Zhang, Chenghao Li, Yu Qiao, Sheng Zheng,, Sumit Kumar Dam, Mengchun Zhang, Jung Uk Kim, Seong Tae Kim, Jinwoo Choi,, Gyeong-Moon Park, Sung-Ho Bae, Lik-Hang Lee, Pan Hui, In So Kweon, Choong, Seon Hong

TL;DR
This paper provides the first comprehensive survey of ChatGPT, covering its technology, applications, challenges, and future prospects for achieving artificial general intelligence through AI-generated content.
Contribution
It offers an extensive review of ChatGPT's underlying technology, applications, challenges, and future evolution towards general-purpose AI-generated content, filling a critical gap in current literature.
Findings
Over 500 articles mention ChatGPT, indicating widespread research interest.
ChatGPT has rapidly gained user adoption and media attention since its release.
The survey discusses potential pathways for ChatGPT to evolve into AGI.
Abstract
OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quickly attracted numerous users with extensive media coverage. Such unprecedented attention has also motivated numerous researchers to investigate ChatGPT from various aspects. According to Google scholar, there are more than 500 articles with ChatGPT in their titles or mentioning it in their abstracts. Considering this, a review is urgently needed, and our work fills this gap. Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges. Moreover, we present an outlook on how ChatGPT might evolve to realize general-purpose AIGC (a.k.a. AI-generated content), which will…
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Topic Modeling · Machine Learning in Healthcare
MethodsMulti-Head Attention · Attention Is All You Need · Label Smoothing · Position-Wise Feed-Forward Layer · Softmax · Linear Layer · Byte Pair Encoding · Layer Normalization · Residual Connection · Dense Connections
