Impact and Importance of LLMOps for Enterprises Advancing Generative AI

In the current landscape of artificial intelligence (AI), the emergence of large language models LLMs has catalyzed the development of generative AI applications across various industries. LLMOps, a specialized subset of MLOps (Machine Learning Operations), is gaining traction as an essential framework for managing and operationalizing LLMs at scale. This article explores the critical role of LLMOps in advancing generative AI within enterprises, addressing the complexities involved in deploying, monitoring, and maintaining these models. It further examines how LLMOps enhances collaboration between data scientists, ML engineers, and IT operations. Promoting a seamless integration of LLMs into existing enterprise infrastructures. The article also highlights the challenges and opportunities that arise with the adoption of LLMOps, offering insights into how organizations can leverage this framework to unlock the full potential of generative AI.

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Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2024-08-05
DOI
https://doi.org/10.21275/sr24808231922
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Impact and Importance of LLMOps for Enterprises Advancing Generative AI

Ejas Ahamed Mohamed Ibrahim
International Journal of Science and Research (IJSR)
Big Data and Business Intelligence
article

Impact and Importance of LLMOps for Enterprises Advancing Generative AI

Ejas Ahamed Mohamed Ibrahim
article en

Abstract

In the current landscape of artificial intelligence (AI), the emergence of large language models LLMs has catalyzed the development of generative AI applications across various industries. LLMOps, a specialized subset of MLOps (Machine Learning Operations), is gaining traction as an essential framework for managing and operationalizing LLMs at scale. This article explores the critical role of LLMOps in advancing generative AI within enterprises, addressing the complexities involved in deploying, monitoring, and maintaining these models. It further examines how LLMOps enhances collaboration between data scientists, ML engineers, and IT operations. Promoting a seamless integration of LLMs into existing enterprise infrastructures. The article also highlights the challenges and opportunities that arise with the adoption of LLMOps, offering insights into how organizations can leverage this framework to unlock the full potential of generative AI.

International Journal of Science and Research (IJSR)Vol. 13(8)
Capgemini (United States) (US)
Decent work and economic growth
Openalex Percentile: Top 81%
Big Data and Business Intelligence
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