LEVERAGING CLOUD INFRASTRUCTURE FOR SCALABLE GENERATIVE AI MODELS: TECHNIQUES FOR EFFICIENT TRAINING AND DEPLOYMENT

Registration ID: IJNRD_300290

Published ID: IJNRD2306656

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Pranav Murthy

Cloud Infrastructure, Generative AI Models, Efficient Training, Distributed Computing, AI-optimized hardware, Serverless Computing. Containerization, Edge Computing

The organization of cloud services combined with generative artificial intelligence models is progressing in the training and construction of artificial intelligence. This paper focuses on how cloud computing can be utilized to fulfill the advanced needs to be met in generative AI and how the applicable approaches can be identified. Training methodologies with distributed systems, resources, and data pipelines and how to put models into production as serverless, containerized models at the edge are part of it. This paper also analyses the other complex structures of hardware that are AI-enabled, such as the GPUs, the TPUs, and the FPGAs, and how to feed these resources most efficiently and cheaply possible. Analyzing the trends for the future, the paper discusses the unique hardware for AI, consolidating AI services into multifunctional platforms, and sustainable trends to provide better progression of the AI-based cloud in the future. The aim is to present a definite picture of the potential of the cloud as an environment for the construction of generative AI models of high scalability and efficiency.

Published Paper   E-Certificate

Pranav Murthy (June-2023). LEVERAGING CLOUD INFRASTRUCTURE FOR SCALABLE GENERATIVE AI MODELS: TECHNIQUES FOR EFFICIENT TRAINING AND DEPLOYMENT. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(6), g842-g851. https://ijnrd.org/papers/IJNRD2306656.pdf

Volume 8 Issue 6, June-2023

Pages : g842-g851

Paper Reg. ID: IJNRD_300290

Published Paper Id: IJNRD2306656

Downloads: 000122008

Research Area: Science and Technology

Author Type: Indian Author

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306656.pdf

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