Gemini versus ChatGPT: applications, performance, architecture, capabilities, and implementation

https://doi.org/10.48185/jaai.v5i1.1052

Authors

  • Nitin Rane University of Mumbai, Mumbai, India
  • Saurabh Choudhary University of Mumbai, Mumbai, India
  • Jayesh Rane University of Mumbai, Mumbai, India

Keywords:

Large language models, Generative Artificial Intelligence, ChatGPT, Gemini, Performance, Architecture, Capabilities.

Abstract

This research paper presents an in-depth comparative examination of Gemini and ChatGPT, two prominent conversational AI models, exploring their respective applications, performance metrics, architectural variances, and overall capabilities. As conversational AI becomes increasingly prevalent across industries, comprehending the nuances of these models becomes pivotal for effective deployment. The paper initiates by outlining the wide array of applications for both Gemini and ChatGPT, spanning industries such as customer service, construction, finance, education, healthcare, and entertainment. It analyzes how each model addresses specific use cases, emphasizing their flexibility and potential impact across different sectors. Following this, the study assesses the performance of Gemini and ChatGPT through both empirical benchmarks and real-world deployment scenarios. Key metrics, including response coherence, accuracy, latency, and scalability, are scrutinized to gauge the models' ability to generate contextually appropriate and coherent responses in conversational contexts. Moreover, the paper elucidates the architectural distinctions between Gemini and ChatGPT, covering variances in training methodologies, model architectures, and underlying technologies. Understanding these architectural nuances provides deeper insights into the computational mechanisms underpinning each model's performance. Lastly, the paper explores the capabilities of Gemini and ChatGPT in handling complex linguistic phenomena, deciphering user intents, and sustaining engaging dialogues over prolonged interactions. This discussion encompasses language generation, sentiment analysis, context retention, and ethical considerations, shedding light on the potential of these models to facilitate meaningful human-computer interactions. Through this thorough comparative analysis, the research contributes to the ongoing conversation surrounding conversational AI systems. It offers valuable insights into the strengths and limitations of Gemini and ChatGPT, empowering stakeholders to make informed decisions regarding their optimal utilization across diverse applications.

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Published

2024-03-20

How to Cite

Rane, N., Choudhary , S. ., & Rane, J. (2024). Gemini versus ChatGPT: applications, performance, architecture, capabilities, and implementation. Journal of Applied Artificial Intelligence, 5(1), 69–93. https://doi.org/10.48185/jaai.v5i1.1052