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Large Fourth-Generation Language Models as a New Tool in Scientific Research
Large Fourth-Generation Language Models as a New Tool in Scientific Research
Annotation

In this study, the latest achievements in the field of deep learning, including convolutional, recurrent, and graph neural networks and attention mechanisms, as well as their contribution to the development of pre-trained language models, are examined. A brief literature review is presented, discussing the use of pre-trained language models in scientific research and education in various fields of science. Experiments are conducted on the application of ChatGPT in the field of economics. The authors present an analysis of the advantages and limitations associated with ChatGPT, providing recommendations for its use in scientific work. Additionally, the article demonstrates the ability of ChatGPT to generate C# programs for agent-based models (ABM) and computable general equilibrium (CGE) models, highlighting its potential for interdisciplinary research and practical applications in economics and computational modeling.

About authors
Alexey Bragin
Central Economics and Mathematics Institute, Russian Academy of Sciences
Albert Bakhtizin
Director, CEMI RAS
Director of CEMI RAS. Head of laboratory of computer simulation of socio-economical processes, CEMI RAS
Valery Makarov
Scientific Director of the Central Economics and Mathematics Institute of the Russian Academy of Sciences
Central economic and mathematical Institute of the Russian Academy of Sciences
References

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