LLMOps: Operationalizing Language Models for the Enterprise

This comprehensive article explores the emerging field of LLMOps (Language Model Operations), a specialized branch of MLOps focused on deploying and managing large language models (LLMs) in production environments. The article examines the LLM lifecycle, challenges in scaling LLMs, essential LLMOps tooling, best practices for effective management, and future trends. Drawing on recent industry studies and statistics, it highlights the growing significance of LLMOps in enterprise AI applications, its potential to streamline operations and reduce costs, and its role in addressing critical issues such as model performance, scalability, data privacy, and ethical AI deployment

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-10-11
DOI
https://doi.org/10.32628/cseit241051044
Primary Topic
Simulation and Modeling Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

LLMOps: Operationalizing Language Models for the Enterprise

Suruchi Shah
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Simulation and Modeling Applications
article

LLMOps: Operationalizing Language Models for the Enterprise

Suruchi Shah
article en

Abstract

This comprehensive article explores the emerging field of LLMOps (Language Model Operations), a specialized branch of MLOps focused on deploying and managing large language models (LLMs) in production environments. The article examines the LLM lifecycle, challenges in scaling LLMs, essential LLMOps tooling, best practices for effective management, and future trends. Drawing on recent industry studies and statistics, it highlights the growing significance of LLMOps in enterprise AI applications, its potential to streamline operations and reduce costs, and its role in addressing critical issues such as model performance, scalability, data privacy, and ethical AI deployment

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(5)
LinkedIn (United States) (US)
Openalex Percentile: Top 80%
Simulation and Modeling Applications
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