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Advancing Scientific Research in Computer Science by ChatGPT and LLaMA—A Review

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Intelligent Manufacturing and Energy Sustainability (ICIMES 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 372))

Abstract

ChatGPT and LLaMA AI Modelling are advancing computer science scientific research in several ways. We discuss the capabilities of ChatGPT and LLaMA to advance computer science research in this review. Whereas LLaMA is an automated dialogue system that can respond to questions about scientific subjects, ChatGPT is an NLP model that can create dialogues. The authors contend that by offering scientists more effective methods for data collection and analysis, these two technologies have the potential to fundamentally alter the way they conduct research. According to the authors, ChatGPT and LLaMA could be used to speed up data collection and analysis and give researchers more accurate findings. Additionally, they propose that similar technologies may be employed to develop virtual assistants for scientists, enabling them to easily access pertinent data and take better decisions. Additionally, they think that these technologies could be utilized to enhance inter-scientist communication, facilitating more productive collaboration. There are many benefits of employing LLaMA and ChatGPT in scientific research. These innovations may shorten the time required for data gathering and analysis while also giving researchers more precise findings. These might also help scientists communicate more effectively with one another, which would improve collaboration. Using these tools for scientific study does have certain restrictions. In the real world, it is unknown, for instance, how trustworthy the outcomes produced by ChatGPT and LLaMA would be. Furthermore, it's not obvious how long it would take to train these models before they could be put to good use in a research environment. Prior to putting AI-based systems into practice in the real world, it is important to consider the ethical issues surrounding their use for scientific study.

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There is no conflict of interest.

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Authors' Contributions

The researchers participated in all parts of the research equally.

Acknowledgements

I would like to thank the ChatGPT for providing some important information., Thanks to the editors and reviewers.

Author information

Authors and Affiliations

  1. Faculty of Artificial Intelligence, Kafrelsheikh University, Kafrelsheikh, 33516, Egypt

    Esraa Hassan & Mahmoud Y. Shams

  2. Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Roheet Bhatnagar

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  1. Esraa Hassan
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  2. Roheet Bhatnagar
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  3. Mahmoud Y. Shams
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Corresponding author

Correspondence to Roheet Bhatnagar .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India

    P. H. V. Sesha Talpa Sai

  2. Department of Mechanical Engineering, Malla Reddy College of Engineering and Technology, Hyderabad, Telangana, India

    Srikar Potnuru

  3. Faculty of Engineering, Department of Civil Engineering, Suleyman Demirel University, Isparta, Türkiye

    Mehmet Avcar

  4. Department of Mechanical Engineering, National Institute of Technology, Jamshedpur, Jharkhand, India

    Vishesh Ranjan Kar

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Hassan, E., Bhatnagar, R., Shams, M.Y. (2024). Advancing Scientific Research in Computer Science by ChatGPT and LLaMA—A Review. In: Talpa Sai, P.H.V.S., Potnuru, S., Avcar, M., Ranjan Kar, V. (eds) Intelligent Manufacturing and Energy Sustainability. ICIMES 2023. Smart Innovation, Systems and Technologies, vol 372. Springer, Singapore. https://doi.org/10.1007/978-981-99-6774-2_3

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  • DOI: https://doi.org/10.1007/978-981-99-6774-2_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-6773-5

  • Online ISBN: 978-981-99-6774-2

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