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The Rise of Multi-Agent LLMs: Insights from Agent Smith and the Challenges of Distributed Data Processing in AI Systems
Soumyodeep Mukherjee
Pages - 1 - 13     |    Revised - 30-09-2024     |    Published - 31-10-2024
Volume - 13   Issue - 1    |    Publication Date - October 2024  Table of Contents
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KEYWORDS
Multi-Agent Systems, Large Language Models, Distributed Data ProcessingDistributed Data Proces, Reinforcement Learning, AI Ethics
ABSTRACT
The emergence of multi-agent systems leveraging large language models (LLMs) represents a significant advancement in artificial intelligence. These systems, characterized by the interaction of multiple autonomous agents, hold the potential to revolutionize various fields, from collaborative problem-solving to autonomous decision-making. In this paper, we draw parallels between these multi-agent LLM systems and the concept of Agent Smith from the "Matrix" series, highlighting the potential, challenges, and ethical considerations of such technologies. By examining these analogies, we propose strategies for managing and mitigating the risks associated with the development and deployment of multi-agent LLM systems.
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Mr. Soumyodeep Mukherjee
Genmab - United States of America
soumyodeep.88@gmail.com


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