•  
  •  
 

Scientific Information Research

Keywords

ChatGPT; GPT model; scientific research; information resource management

Abstract

[Purpose/significance]The emergence of ChatGPT has brought significant changes to the whole society, and to this day, its impact is still spreading, Experts, scholars and news media have broadly discussed it. As a major progress in the field of natural language processing, ChatGPT carries too much attention and expectations. As an important battlefield in the field of natural language processing, information resource management should give full play to the advantages of disciplines under this technological change and drive the development of disciplines with technology.[Method/process] Starting from the origin of ChatGPT, this paper introduces the development path of GPT model, and summarizes and summarizes its impact on society and academia.[Result/conclusion]In general, the development of large language models represented by ChatGPT has promoted the process of social digitalization. As an emerging discipline with strong intersectionality, information resource management should balance the relationship between theory research and technical practice.In the wave of the new era, we should actively embrace new technologies and expand the application field of technology.

First Page

37

Reference

[1] BAHDANAU D,CHO K,BENGIO Y.Neural machine translation by jointly learning to align and translate[C]//Advances in International Conference on Learning Representations,San Diego,CA:2015.
[2] VASWANI A,SHAZEER N,PARMAR N,et al. Attention is all you need[C]//31st Conference on Neural Information Processing Systems,Long Beach,CA:2017.
[3] DEVLIN J,CHANG MW,LEE K,et al.Bert:Pre-training of deep bidirectional transformers for language understanding[J].arXiv preprint arXiv:1810.04805,2018.
[4] RADFORD A,NARASIMHAN K,SALIMANS T,et al.Improving language understanding by generative pre-training[J].Computer Science,2018:1-12.
[5] MARTINDALE J.How to use Google Bard,the latest AI chatbot service[EB/OL].(2023-03-21)[2023-03-23].https://www.digitaltrends.com/computing/how-to-use-google-bard/.
[6] OpenAI.Introducing ChatGPT[EB/OL].(2022-11-30)[2023-03-07].https://openai.com/blog/chatgpt.
[7] MCCANN B,BRADBURY J,XIONG C,et al.Learned in translation:Contextualized word vectors[C]//31st Conference on Neural Information Processing Systems,Long Beach,CA:2017.
[8] RADFORD A,WU J,CHILD R,et al.Language models are unsupervised multitask learners[J].OpenAI blog, 2019,1(08):9.
[9] ZIEGLER D M,STIENNON N,WU J,et al.Fine-tuning language models from human preferences[J].arXiv preprint arXiv:1909.08593,2019.
[10] KAELBLING L P,LITTMAN M L,MOORE A W.Reinforcement learning:A survey[J].Journal of artificial intelligence research,1996,4:237-285.
[11] NAKANO R,HILTON J,BALAJI S,et al.Webgpt:Browser-assisted question-answering with human feedback[J]. arXiv preprint arXiv:2112.09332v3,2021.
[12] OUYANG L,WU J,JIANG X,et al.Training language models to follow instructions with human feedback[J]. arXiv preprint arXiv:2203.02155,2022.
[13] OpenAI.An API for accessing new AI models developed by OpenAI[EB/OL].[2023-03-21].https://latform.openai.com.
[14] CHRISTIANO P F,LEIKE J,BROWN T,et al.Deep reinforcement learning from human preferences[J].arXiv:1706.03741,2017.
[15] SCHULMAN J,WOLSKI F,DHARIWAL P,et al.Proximal policy optimization algorithms[J].arXiv preprint arXiv:1707.06347,2017.
[16] JOYCE J M.International encyclopedia of statistical science:Kullback-leibler divergence[M].New York:Springer,2011:720-722.
[17] 澎湃思想市场.乔姆斯基:ChatGPT的虚假承诺[EB/OL].[2023-03-11].http://mp.weixin.qq.com/s?__biz=MzU4NzQ4OTYzMA==&mid=2247509338&idx=1&sn=c04b7eb982a2cc3ba5153e1d4d0cb7d1&chksm=fde9ad6
bca9e247df0cc6e6e5d98dc552a2e14fb4d146c6499e61ec6bcb414f55ecc8be276cd#rd.
[18] Official Microsoft Blog.Reinventing search with a new AI-powered Microsoft Bing and Edge,your copilot for the web[EB/OL].The Official Microsoft Blog.(2023-02-07)[2023-03-11].https://blogs.microsoft.com/blog/2023/02/07/reinventing-search-with-a-new-ai-powered-microsoft-bing-and-edge-your-copilot-for-the-web.
[19] 百度正式发布文心一言,李彦宏现场Demo演示“五大能力”_10%公司_澎湃新闻-The Paper[EB/OL]. [2023-03-21].https://www.thepaper.cn/newsDetail_forward_22322022.
[20] OpenAI.Introducing ChatGPT and Whisper APIs[EB/OL].(2023-03-01)[2023-03-12].https://openai.com/blog/introducing-chatgpt-and-whisper-apis.
[21] WARREN T.Microsoft is looking at OpenAI's GPT for Word,Outlook,and PowerPoint[EB/OL]//The Verge.(2023-01-09)[2023-03-12].https://www.theverge.com/2023/1/9/23546144/microsoft-openai-word-powerpoint-outlook-gpt-integration-rumor.
[22] JEBLICK K,SCHACHTNER B,DEXL J,et al.ChatGPT Makes medicine easy to swallow:an exploratory case study on simplified radiology reports[J].arXiv preprint arXiv:2212.14882,2022.
[23] KHAN R A,JAWAID M,KHAN A R,et al.ChatGPT-reshaping medical education and clinical management[J].Pakistan Journal of Medical Sciences,2023,39(02):605-607.
[24] 张志祯,张玲玲,米天伊,等.大型语言模型会催生学校结构性变革吗?:基于ChatGPT的前瞻性分析[J/OL].中国远程教育.(2023-03-03)[2023-03-20].https://kns.cnki.net/kcms/detail//11.4089.G4.20230301.1646.004.html.
[25] 周洪宇,李宇阳.ChatGPT对教育生态的冲击及应对策略[J].新疆师范大学学报(哲学社会科学版),2023,44(04):134-143.
[26] ANONYMOUS.Tools such as ChatGPT threaten transparent science;here are our ground rules for their use[J].Nature,2023,613(7945):612-612.
[27] THORP H H.ChatGPT is fun,but not an author[J].Science,2023,379(6630):313-313.
[28] VAN DIS E A,BOLLEN J,ZUIDEMA W,et al.ChatGPT:five priorities for research[J].Nature,2023,614(7947):224-226.
[29] 邓建鹏,朱怿成.ChatGPT模型的法律风险及应对之策[J].新疆师范大学学报(哲学社会科学版),2023,44(05):41-51.
[30] OpenAI.GPT-2 Output Detector | Discover AI use cases[EB/OL].[2023-03-12].https://gpt3demo.com/apps/gpt-2-output-detector.
[31] 中国科学网.“高分子版ChatGPT”加速高性能材料研制[EB/OL].(2023-03-09)[2023-03-12].https://finance.sina.com.cn/jjxw/2023-03-09/doc-imykhmqu9992116.shtml.
[32] LIN Z,AKIN H,RAO R,et al.Evolutionary-scale prediction of atomic-level protein structure with a language model[J].Science,2023,379(6637):1123-1130.
[33] LIN Q,MAO R,LIU J,et al.Fusing topology contexts and logical rules in language models for knowledge graph completion[J].Information Fusion,2023,90:253-264.
[34] SALABERRIA A,AZKUNE G,DE LACALLE O L,et al.Image captioning for effective use of language models in knowledge-based visual question answering[J].Expert Systems with Applications,2023,212:118669.
[35] 蒋华林.人工智能聊天机器人对科研成果与人才评价的影响研究:基于ChatGPT、Microsoft Bing视角分析[J/OL].重庆大学学报(社会科学版).(2023-03-09)[2023-03-20].https://kns.cnki.net/kcms/detail/50.1023.C.20230309.1355.002.html.
[36] JERONYMO V,BONIFACIO L,ABONIZIO H,et al.InPars-v2:large language models as efficient dataset generators for information retrieval[J].arXiv preprint arXiv:2301.01820,2023.
[37] 比特人文.古文智能处理成果之五:四库全书SikuGPT正式发布[EB/OL].[2023-03-14].http://mp.weixin.qq.com/s?__biz=MzU5NjM0MjE3MA==&mid=2247505464&idx=1&sn=7b1cb1154d2aeffae88bcdb7a10cfc09&
chksm=fe66b2cdc9113bdb303218447f3aa6d14d6b43b6241724d7380ac0982904b9c17bb23f6a3dc1#rd.
[38] IT之家.复旦大学MOSS团队:MOSS参数规模约是ChatGPT的1/10[EB/OL].[2023-03-16].https://new.qq.com/rain/a/20230302A024XI00.
[39] MCMAHAN B,MOORE E,RAMAGE D,et al.Communication-efficient learning of deep networks from decentralized data[C]//Proceeding of the 20th International Conference on Artificial Intelligence and Statistics.For Lauderdale,Flordia:2017.
[40] OpenAI.GPT-4 is OpenAI's most advanced system,producing safer and more useful responses[EB/OL].[2023-03-21].https://openai.com/product/gpt-4.
[41] DRIESS D,XIA F,SAJJADI M S,et al.PaLM-E:an embodied multimodal language model[J].arXiv preprint arXiv:2303.03378,2023.
[42] WAHLE J P.A cohesive distillation architecture for neural language models[J].arXiv preprint arXiv:2301.08130,2023.

Share

COinS