From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools
PDF

Keywords

AI
ChatGPT-3
GPT-4
GPT-5
Google's BARD
LLM
NLP

How to Cite

Rahaman, M. S., Ahsan , M. M. T., Anjum, N., Terano, H. J. R., & Rahman, M. M. (2023). From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools. Journal of Engineering and Emerging Technologies, 2(1), 1–11. https://doi.org/10.52631/jeet.v2i1.188

Abstract

Recent improvements in Natural Language Processing (NLP) have led to the creation of powerful language models like Chat Generative Pre-training Transformer (ChatGPT), Google’s BARD, Ernie which has shown to be very good at many different language tasks. But as language tasks get more complicated, having even more advanced NLP tool is essential nowadays. In this study, researchers look at how the latest versions of the GPT language model(GPT-4 & 5) can help with these advancements. The research method for this paper is based on a narrative analysis of the literature, which makes use of secondary data gathered from previously published studies including articles, websites, blogs, and visual and numerical facts etc. Findings of this study revealed that GPT-4 improves the model's training data, the speed with which it can be computed, the flawless answers that it provides with, and its overall performance. This study also shows that GPT-4 does much better than GPT-3.5 at translating languages, answering questions, and figuring out how people feel about things. The study provides a solid basis for building even more advanced NLP tools and programmes like GPT-5. The study will help the AI & LLM researchers, NLP developers and academicians in exploring more into this particular field of study. As this is the first kind of research comparing two NLP tools, therefore researchers suggested going for a quantitative research in the near future to validate the findings of this research.

https://doi.org/10.52631/jeet.v2i1.188
PDF

References

Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152

Ahmed, N., & Wahed, M. (2020). The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research. arXiv. https://doi.org/10.48550/arXiv.2010.15581

Aladakatti, S. S., & Senthil Kumar, S. (2023). Exploring natural language processing techniques to extract semantics from unstructured dataset which will aid in effective semantic interlinking. International Journal of Modeling, Simulation, and Scientific Computing, 14(1), 2243004. https://doi.org/10.1142/S1793962322430048

Arya , N. (2023). GPT-4: Everything You Need To Know. In KDnuggets. https://www.kdnuggets.com/gpt-4-everything-you-need-to-know.html

Bang, Y., Cahyawijaya, S., Lee, N., Dai, W., Su, D., Wilie, B., Lovenia, H., Ji, Z., Yu, T., Chung, W., Do, Q. V., Xu, Y., & Fung, P. (2023). A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity. arXiv. http://arxiv.org/abs/2302.04023

Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S., Nori, H., Palangi, H., Ribeiro, M. T., & Zhang, Y. (2023). Sparks of Artificial General Intelligence: Early experiments with GPT-4. arXiv. http://arxiv.org/abs/2303.12712

Capelouto, J. D. (2023). Here’s how GPT-4 scored on the GRE, LSAT, AP English, and other exams | Semafor. https://www.semafor.com/article/03/15/2023/how-gpt-4-performed-in-academic-exams

ChatGPT: Everything you need to know about OpenAI’s GPT-4 tool. (n.d.). In BBC Science Focus Magazine. https://www.sciencefocus.com/future-technology/gpt-3/

ChatGPT response, Prompt: Write a beautiful quote on the title: But, people must have to be tech-savvy. (2023). In ChatGPT . https://help.openai.com/en/articles/6825453-chatgpt-release-notes

Choi, J. H., Hickman, K. E., Monahan, A., & Schwarcz, D. B. (2023). ChatGPT Goes to Law School. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4335905

Coughlan, M., Cronin, P., & Ryan, F. (2007). Step-by-step guide to critiquing research. Part 1: quantitative research. British Journal of Nursing, 16(11), 658–663. https://doi.org/10.12968/bjon.2007.16.11.23681

Fitria, T. N. (2023). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum Journal of English Language Teaching, 12, 44–58. https://doi.org/10.15294/elt.v12i1.64069

Frąckiewicz, M. (2023). OpenAI and Its Role in the Evolution of Natural Language Processing – TS2 SPACE. https://ts2.space/en/openai-and-its-role-in-the-evolution-of-natural-language-processing/

Goncharenko, V. (2023). GPT-4 Outperforms All Existing Large Language Models. In Metaverse Post. https://mpost.io/gpt-4-outperforms-all-existing-large-language-models/

Hughes, A. (n.d.). ChatGPT: Everything you need to know about OpenAI’s GPT-4 tool. In BBC Science Focus Magazine. Retrieved May 3, 2023, from https://www.sciencefocus.com/future-technology/gpt-3/

Jiang, K., & Lu, X. (2020). Natural Language Processing and Its Applications in Machine Translation: A Diachronic Review. 2020 IEEE 3rd International Conference of Safe Production and Informatization (IICSPI), 210–214. https://doi.org/10.1109/IICSPI51290.2020.9332458

Juhn, Y., & Liu, H. (2020). Artificial intelligence approaches using natural language processing to advance EHR-based clinical research. Journal of Allergy and Clinical Immunology, 145(2), 463–469. https://doi.org/10.1016/j.jaci.2019.12.897

Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023). Natural language processing: state of the art, current trends and challenges. Multimedia Tools and Applications, 82(3), 3713–3744. https://doi.org/10.1007/s11042-022-13428-4

Kosinski, M. (2023). Theory of Mind May Have Spontaneously Emerged in Large Language Models. arXiv. http://arxiv.org/abs/2302.02083

Liu, Z., Yu, X., Zhang, L., Wu, Z., Cao, C., Dai, H., Zhao, L., Liu, W., Shen, D., Li, Q., Liu, T., Zhu, D., & Li, X. (2023). DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4. arXiv. http://arxiv.org/abs/2303.11032

Nori, H., King, N., McKinney, S. M., Carignan, D., & Horvitz, E. (2023). Capabilities of GPT-4 on Medical Challenge Problems. arXiv. http://arxiv.org/abs/2303.13375

Oberleiter, A. (2023). ChatGPT 4& AI: The Truth! and a Practical Chat GPT guide [Online learning and teaching marketplace]. In Udemy.com. https://www.udemy.com/course/chatgpt-programming-and-social-media-marketing-with-chatgpt/

OpenAI. (2023). GPT-4 Technical Report. arXiv. https://doi.org/10.48550/arXiv.2303.08774

Otter, D. W., Medina, J. R., & Kalita, J. K. (2019). A Survey of the Usages of Deep Learning in Natural Language Processing. arXiv. https://doi.org/10.48550/arXiv.1807.10854

Peng, B., Li, C., He, P., Galley, M., & Gao, J. (2023). Instruction Tuning with GPT-4. arXiv. http://arxiv.org/abs/2304.03277

Rahaman, M. S. (2023). Can ChatGPT be your friend? Emergence of Entrepreneurial Research [SSRN Scholarly Paper]. https://doi.org/10.2139/ssrn.4368541

Rahaman, M. S., Ahsan, M. M. T., Anjum, N., Rahman, M. M., & Rahman, M. N. (2023). The AI Race is on! Google’s Bard and OpenAI’s ChatGPT Head to Head: An Opinion Article [SSRN Scholarly Paper]. https://doi.org/10.2139/ssrn.4351785

Rahman, M., Terano, H. J. R., Rahman, N., Salamzadeh, A., & Rahaman, S. (2023). ChatGPT and Academic Research: A Review and Recommendations Based on Practical Examples. Journal of Education, Management and Development Studies, 3(1), 1–12. https://doi.org/10.52631/jemds.v3i1.175

Raina, V., & Krishnamurthy, S. (2022). Natural Language Processing. In Building an Effective Data Science Practice (pp. 63–73). Apress. https://doi.org/10.1007/978-1-4842-7419-4_6

Rangapur, A., & Wang, H. (2023). ChatGPT-Crawler: Find out if ChatGPT really knows what it’s talking about. arXiv. http://arxiv.org/abs/2304.03325

Roose, K. (2023). How ChatGPT Kicked Off an A.I. Arms Race. The New York Times. https://www.nytimes.com/2023/02/03/technology/chatgpt-openai-artificial-intelligence.html

Rotman, D. (n.d.). ChatGPT is about to revolutionize the economy. We need to decide what that looks like. In MIT Technology Review. Retrieved May 3, 2023, from https://www.technologyreview.com/2023/03/25/1070275/chatgpt-revolutionize-economy-decide-what-looks-like/

Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1). https://doi.org/10.37074/jalt.2023.6.1.9

Shahriar, S., & Hayawi, K. (2023). Let’s have a chat! A Conversation with ChatGPT: Technology, Applications, and Limitations. arXiv. http://arxiv.org/abs/2302.13817

Teebagy, S., Colwell, L., Wood, E., Yaghy, A., & Faustina, M. (2023). Improved Performance of ChatGPT-4 on the OKAP Exam: A Comparative Study with ChatGPT-3.5 [Preprint]. Ophthalmology. https://doi.org/10.1101/2023.04.03.23287957

Thiergart, J., Huber, S., & Übellacker, T. (2021). Understanding Emails and Drafting Responses – An Approach Using GPT-3. arXiv. http://arxiv.org/abs/2102.03062

Tiwari, N. (2023). Ernie Bot vs. ChatGPT: A Comparative Analysis of AI-Language Models. In Analytics Vidhya. https://www.analyticsvidhya.com/blog/2023/03/ernie-bot-vs-chatgpt-a-comparative-analysis-of-ai-language-models/

Truly, A. (2023). GPT-4: how to use, new features, availability, and more. In Digital Trends. https://www.digitaltrends.com/computing/chatgpt-4-everything-we-know-so-far/

Varghese, A. (2023). GPT-4: Everything about the OpenAI’s newly introduced large language model. In Business Standard. https://www.business-standard.com/article/technology/gpt-4-everything-about-the-openai-s-newly-introduced-large-language-model-123031500690_1.html

Ventresca, M., & Mohr, J. (2002). Archival Research Methods (pp. 805–828). https://doi.org/10.1002/9781405164061.ch35

Wang, J., Liang, Y., Meng, F., Zou, B., Li, Z., Qu, J., & Zhou, J. (2023). Zero-Shot Cross-Lingual Summarization via Large Language Models. arXiv. http://arxiv.org/abs/2302.14229

Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., Davison, J., Shleifer, S., von Platen, P., Ma, C., Jernite, Y., Plu, J., Xu, C., Le Scao, T., Gugger, S., … Rush, A. (2020). Transformers: State-of-the-Art Natural Language Processing. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 38–45. https://doi.org/10.18653/v1/2020.emnlp-demos.6

Zarifhonarvar, A. (2023). Economics of ChatGPT: A Labor Market View on the Occupational Impact of Artificial Intelligence [SSRN Scholarly Paper]. https://doi.org/10.2139/ssrn.4350925

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Copyright (c) 2023 Journal of Engineering and Emerging Technologies