Algorithmic Issues, Challenges, and Theoretical Concerns of ChatGPT-Reference-Cited by-同舟云学术

Algorithmic Issues, Challenges, and Theoretical Concerns of ChatGPT

Published:2024-05-28 Issue: Volume: Page:56-74
ISSN:2327-0411
Container-title:Advances in Computational Intelligence and Robotics
language:
Short-container-title:

Author:

Patil Pradnya¹^ORCID,Kulkarni Kaustubh²^ORCID,Sharma Priyanka³^ORCID

Affiliation:

1. K.J. Somaiya Institute of Technology, Mumbai, India

2. K.J. Somaiya College of Engineering, Somaiya University, Mumbai, India

3. Swami Keshvanand Institute of Technology, Management, and Gramothan, India

Abstract

Large language model (LLM) ChatGPT has made tremendous progress in natural language processing (NLP), especially in human-quality text production, multilingual translation, and content creation. However, because of its extensive use, algorithmic issues, challenges, and theoretical queries come up. Fairness, bias, explainability, generalization, originality, inventiveness, and safety are the main topics of this study's examination of ChatGPT's intricate theoretical and algorithmic components. It looks into the possibility of explainability, transferability, generalization, bias in the data, and the model's capacity to provide original and imaginative content. It also covers possible issues including harmful use, disseminating incorrect information, and offensive or misleading content. These limitations can be addressed so that ChatGPT can be improved to provide LLMs that are more dependable, accountable, and long-lasting while posing no needless risks.

Publisher

IGI Global

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