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Published Paper Details:
Establishing Data Pipelines for Tracking GenAI Usage and Performance
Authors
Shilesh Karunakaran,Dr Rupesh Kumar Mishra
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Keywords
Generative AI, data pipelines, performance monitoring, real-time data integration, AI performance metrics, system efficiency, computational resource usage, data engineering, AI monitoring, performance optimization, scalability, real-time analysis, user interaction.
Abstract
The rapid evolution of generative artificial intelligence (GenAI) has witnessed extensive application across industry sectors, bringing in new technologies and changes in business model deployment. Though its widespread applicability, more development of efficient pipelines to track the usage and performance of these tools is needed to enhance the integration of GenAI technology in organizational systems. This paper seeks to balance the need in current methodology and frameworks dedicated to tracking the performance metrics for GenAI systems with specific reference to real-time integration of data, accuracy, and scalability. Most current practices of measuring the performance of AI overlook the nature of GenAI application, i.e., its requirement to learn and adapt continuously, in addition to requiring multiple data inputs. Most importantly, the absence of measurable benchmarks for measuring GenAI output only makes measurement more challenging. This study proposes the development and deployment of data pipelines that enable the gathering, processing, and analysis of GenAI usage and performance metrics. The proposed pipelines are designed to provide comprehensive insights into system efficiency, output quality, user engagement, and computational resource usage. Through the application of cutting-edge data engineering techniques, such as automated data gathering and real-time performance monitoring, this study offers a framework for increasing the transparency and accountability of GenAI applications. The findings of this study will guide the development of resilient monitoring systems that can be integrated into various GenAI-powered platforms, guaranteeing optimal performance and well-informed decision-making. The findings of this study have the potential to guide future advancements in GenAI deployment and management, paving the way for more reliable and effective AI-powered solutions.
IJCRT's Publication Details
Unique Identification Number - IJCRT2502999
Paper ID - 281871
Author type - Indian Author
Page Number(s) - i436-i455
Pubished in - Volume 13 | Issue 2 | February 2025
DOI (Digital Object Identifier) -
No Of Downloads - 81
Author Country - India, -, -, -, -, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
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Shilesh Karunakaran,Dr Rupesh Kumar Mishra, "Establishing Data Pipelines for Tracking GenAI Usage and Performance", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 2, pp.i436-i455, February 2025, Available at :http://www.ijcrt.org/papers/IJCRT2502999.pdf
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