Generative AI Models and eir Potential Business Use Cases
Ravi Shankar Koppula*
Ravi Shankar Koppula, USA
Citation: Koppula RS. Generative AI Models and eir Potential Business Use Cases. J Artif Intell Mach Learn & Data Sci 2023,
1(4), 333-337. DOI: doi.org/10.51219/JAIMLD/ravi-shankar-koppula/101
Received: 03 December, 2023; Accepted: 28 December, 2023; Published: 30 December, 2023
*Corresponding author: Ravi Shankar Koppula, USA, E-mail: Ravikoppula100@gmail.com
Copyright: © 2023 Koppula RS. Enhancing Supplier Relationships: Critical Factors in Procurement Supplier Selection.., is is
an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use,
distribution, and reproduction in any medium, provided the original author and source are credited.
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A B S T R A C T
Generative Artificial Intelligence (AI) models have emerged as highly efficient and powerful tools capable of producing a
wide range of content, accurately imitating human actions, and generating authentic, high-quality data. is study meticulously
examines the field of generative AI, delving deep into its mechanisms, progression, and advancements that have revolutionized
industries. Furthermore, it explores various business opportunities where these models can be effectively utilized to drive
innovation, enhance productivity, and achieve success. ese opportunities include content generation, data augmentation,
virtual assistants, creative design, predictive analytics, personalization, and decision support systems. e study also assesses the
utilization and functionality of Language Models (LLMs) in generative AI, highlighting their effectiveness in generating realistic
and contextually appropriate content across industries like marketing, advertising, entertainment, healthcare, finance, education,
and manufacturing. e aim of this abstract is to provide a comprehensive overview of generative AI models and their practical
applications in the business sector, government agencies, and non- profit organizations. By offering insights and cutting-edge
research findings, it equips researchers, entrepreneurs, policymakers, and industry professionals with the knowledge to effectively
harness the potential of these technologies. In conclusion, this study serves as a pivotal resource for understanding generative AI
models and their transformative potential, empowering individuals, teams, and organizations to embrace, adopt, and capitalize
on these state-of-the-art technologies, ultimately leading to increased efficiency, productivity, and competitiveness in a rapidly
evolving digital landscape.
Keywords: Generative AI, LLMs, Generative AI use cases
Research Article
Vol: 1 & Iss: 4
https://urfpublishers.com/journal/artificial-intelligence
Journal of Artificial Intelligence, Machine Learning and Data Science
ISSN: 2583-9888
DOI: doi.org/10.51219/JAIMLD/ravi-shankar-koppula/101
Introduction
Generative AI pertains to the subfield of artificial intelligence
that specializes in the production of original content. Its
emphasis lies in computers andsystems using models to generate
a diverse range of content, encompassing images, text, music,
code, synthetic data, and more. Generative AI builds upon a
specific category of AI model called a generative model, which
approximates the fundamental data through mathematical
means. These models take substantial datasets, including
images, text, and sound, as input. Subsequently, a deep learning
model is employed to discern patterns within the data during
the subsequent phase. Once the models have completed their
learning process, they can be effectively utilized for various
pivotal tasks. These tasks consist of generating synthetic images
based on existing ones, modifying or creating new images via
the utilization of a particular image style, facilitating translation,
generating question and answer pairs, and comprehending the
intent or meaning behind text. Furthermore, generative AI can
also convert audio snippets into text or transcribe music, among
other capabilities
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