Comparison of ChatGPT and Bard for using in hybrid intelligent information systems

Abstract

The purpose of this paper is to conduct research and comparative analysis of modern large language models, in particular, such as ChatGPT and Google Bard. As part of the research, the analysis of the advantages and disadvantages of advanced artificial intelligence technologies in various fields of application was carried out. Optimal conditions for using these models were identified, and methods for overcoming the identified shortcomings of large language models based on the mivar approach were proposed. Special attention is paid to the areas of application of large language models, such as providing a quick and effective response to user requests, as well as their use in training and staff adaptation tasks. This paper analyzes large language models, taking into account their integration methods, as well as the possibilities of creating personalized systems for automating communications. The research results include an analysis and comparison of the capabilities of LLM and identifying their advantages and disadvantages with a focus on the problem of “hallucinations”. The paper also proposes hypotheses about the potential overcoming of LLM limitations using the mivar approach. The results of experiments with ChatGPT confirm the relevance of creating structured knowledge and automating the process of building mivar data models, as well as indicate the prospects for combining LLM and the mivar approach. This can reduce the likelihood of generating erroneous information, increase the interpretability of results, and ensure more effective use of language models in various scenarios of artificial intelligence use.