GPT类技术应用开启智能信息处理之颠覆性变革

图书馆杂志 ›› 2023, Vol. 42 ›› Issue (385): 9-13.

GPT类技术应用开启智能信息处理之颠覆性变革

王静静1 叶鹰2, 3, 4 王婉茹5 （1 山东大学新闻传播学院 2 复旦大学国家智能评价与治理实验基地 3 南京大学江苏省国际联合信息学实验室 4 南京大学信息管理学院 5 浙江财经大学信息管理与人工智能学院）

出版日期:2023-05-15 发布日期:2023-05-24
作者简介:王静静山东大学新闻传播学院，副研究员。研究方向：智能信息处理、信息扩散。作者贡献：论文撰写及修改、资料搜集。E-mail：jingjingwang@sdu.edu.cn 山东济南 250100 叶鹰复旦大学国家智能评价与治理实验基地，特聘研究员。研究方向：智能信息处理、定量信息分析。作者贡献：论文选题、撰写及修改。上海 200433 王婉茹浙江财经大学信息管理与人工智能学院，讲师。研究方向：定量信息分析。作者贡献：论文撰写及修改、资料搜集。浙江杭州 310018

Subversive Change for Intelligent Information Processing by the Application of GPT-Type Technology

Wang Jingjing1, Ye Ying2, 3, 4, Wang Wanru 5 (1 School of Journalism and Communication, Shandong University; 2 National Institute of Intelligent Evaluation and Governance, Fudan University; 3 International Joint Informatics Laboratory, Nanjing University; 4 School of Information Management, Nanjing University; 5 School of Information Management and Artificial Intelligence, Zhejiang University of Finance & Economics)

Online:2023-05-15 Published:2023-05-24
About author:Wang Jingjing1, Ye Ying2, 3, 4, Wang Wanru 5 (1 School of Journalism and Communication, Shandong University; 2 National Institute of Intelligent Evaluation and Governance, Fudan University; 3 International Joint Informatics Laboratory, Nanjing University; 4 School of Information Management, Nanjing University; 5 School of Information Management and Artificial Intelligence, Zhejiang University of Finance & Economics)

摘要/Abstract

摘要： 本文在浅析GPT类技术影响智能信息处理的主要方式基础上，提示多模态大模型正在给智能信息处理带来颠覆性变革，主要体现在大模型、多模态、跨语言等方面。文本生成、智能对话、机器翻译等波及智能信息处理的颠覆性应用将对信息处理的自动分析、提取、生成和决策带来巨大的效率提升，从而带来智能信息处理的颠覆性变革。目前，这一革命浪潮正以不可阻挡之势席卷而来，学界和业界须高度关注并积极应对GPT类技术应用开启的智能信息处理革命。

Abstract: Based on the concise analysis of the main ways in which GPT-type technology influences intelligent information processing, this article points out that multimodal large-scale models are bringing disruptive changes to intelligent information processing. These changes are reflected in the aspects of large-scale models, multimodality, and cross-language; and the subversive applications of intelligent information processing will involve fields such as text generation, intelligent dialogue, and machine translation. While describing the related applications phenomenally, the article reminds academia and industry to pay attention to the fact that the application of GPT-type technology is ushering in a revolution in intelligent information processing.

王静静叶鹰王婉茹（山东大学新闻传播学院复旦大学国家智能评价与治理实验基地南京大学江苏省国际联合信息学实验室南京大学信息管理学院浙江财经大学信息管理与人工智能学院）. GPT类技术应用开启智能信息处理之颠覆性变革[J]. 图书馆杂志, 2023, 42(385): 9-13.

Wang Jingjing, Ye Ying, Wang Wanru ( School of Journalism and Communication, Shandong University, National Institute of Intelligent Evaluation and Governance, Fudan University, International Joint Informatics Laboratory, Nanjing University, School of Information Management, Nanjing University, School of Information Management and Artificial Intelligence, Zhejiang University of Finance & Economics). Subversive Change for Intelligent Information Processing by the Application of GPT-Type Technology[J]. Libraly Journal, 2023, 42(385): 9-13.

参考文献

[ 1 ] 叶鹰. 智能信息处理和智能信息分析前瞻 [J]. 图书与情报，2017 （6）： 70–3；95.
[ 2 ] 郑家恒. 智能信息处理[M]. 北京：科学出版社，2010.
[ 3 ] Brockman G，Cheung V，Pettersson L，et al. Openai gym[J]. arXiv preprint arXiv：1606.01540，2016.
[ 4 ] Vaswani A，Shazeer N，Parmar N，et al. Attention is all you need[J]. Advances in Neural Information Processing Systems，2017，30： 5998–6008.
[ 5 ] Radford A，Narasimhan K，Salimans T，et al. Improving language understanding by generative pre-training [OL]. [2023-03-29]. https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf.
[6] Brown T，Mann B，Ryder N，et al. Language models are few-shot learners [J]. Advances in Neural Information Processing Systems，2020，33：
1877–1901.
[ 7 ] Bubeck S，Chandrasekaran V，Eldan R，et al. Sparks of Artificial General Intelligence： Early experiments with GPT-4[J]. arXiv preprint arXiv：2303.12712，2023.
[ 8 ] OpenAI. GPT-4 technical report [J]. arXiv preprint arXiv：2303.08774，2023.
[ 9 ] Else H. Abstracts written by ChatGPT fool scientists [J]. Nature，2023，613： 423.
[10] Sun Y，Wang S，Feng S，et al. Ernie 3.0： Large-scale knowledge enhanced pre-training for language understanding and generation[J]. arXiv preprint arXiv：2107.02137，2021.
[11] Zeng W，Ren X，Su T，et al. PanGu-α： large-scale autoregressive pretrained Chinese language models with auto-parallel computation[J]. arXiv preprint arXiv：2104.12369，2021.
[12] Devlin J，Chang M W，Lee K，et al. Bert： Pre-training of deep bidirectional transformers for language understanding[J]. arXiv preprint arXiv：1810.04805，2018.
[13] Liu Y，Ott M，Goyal N，et al. Roberta： A robustly optimized bert pretraining approach[J]. arXiv preprint arXiv：1907.11692，2019.
[14] Gao C A，Howard F M，Markov N S，et al. Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector，plagiarism detector，and blinded human reviewers[J]. bioRxiv，2022： 2022.12. 23.521610.
[15] Stokel-Walker C，Van Noorden R. What ChatGPT and generative AI mean for science [J]. Nature，2023，614： 214–216.
[16] Bockting C，Van Dis E A M，Bollen J，et al. ChatGPT： five priorities for research [J]. Nature，2023，614： 224–226.