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Analyzing the Landscape of Large Language Models: A Comparative Study.

Large Language Models (LLMs) have emerged as a transformative force in computerized language processing, demonstrating formidable capabilities in understanding intricate linguistic patterns and generating logical and contextually appropriate responses. Artificial intelligence (AI) has led to the development of LLMs, which are now highly effective tools for a variety of applications. The continued application of LLMs in daily life and research emphasizes how crucial it is to evaluate their effects on particular tasks as well as society. This paper looks into the fundamental concepts of LLMs. We start out by covering the development of LLMs ove

By Dr. Dhara A. Darji, Ms. Pooja D. PancholiResearch paper

Resource information

Authors
Dr. Dhara A. Darji, Ms. Pooja D. Pancholi
Research area
Artificial intelligence
Research topics
LLMs, GPT, OpenAI, LlaMa, NLP
Publication date
2024
DOI
10.5281/zenodo.12704094
Upstream last modified
Jul 10, 2024
License
Creative Commons Attribution 4.0 International
Last record update
Nov 5, 2026

About this resource

Large Language Models (LLMs) have emerged as a transformative force in computerized language processing, demonstrating formidable capabilities in understanding intricate linguistic patterns and generating logical and contextually appropriate responses. Artificial intelligence (AI) has led to the development of LLMs, which are now highly effective tools for a variety of applications. The continued application of LLMs in daily life and research emphasizes how crucial it is to evaluate their effects on particular tasks as well as society. This paper looks into the fundamental concepts of LLMs. We start out by covering the development of LLMs over time and their history. After that, we go over the many uses for LLMs. The various LLMs and their comparative analysis are the topic of our next discussion. Lastly, we wrap up by outlining the direction of LLMs research and the issues that still need to be resolved to improve the dependability and utility of this technology.