Problems And Solutions in Developing Scalable Data Infrastructure for Generative AI Models

Chandrababu Kuraku; Shravan Kumar Rajaram; Hemanth Kumar Gollangi

doi:10.63665/ijmlaidse-y1f1a003

Problems And Solutions in Developing Scalable Data Infrastructure for Generative AI Models

Chandrababu Kuraku, Shravan Kumar Rajaram, Hemanth Kumar Gollangi

DOI: 10.63665/ijmlaidse-y1f1a002

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Abstract

Recent growth in generative AI models shows that strong and scalable data infrastructures are crucial for handling large datasets and computationally intensive processes. This paper discusses specific challenges in the design of such infrastructures including real time access, processing, storage, and retrieval of data. We review methods so far adopted and propose appropriate ways of constructing architectures that are dependable, scalable, and efficient. This paper goes into details of how to develop data infrastructures best optimized for generative AI applications based on case studies and current industrial standards.

Keywords

Generative AI, Data Infrastructure, Scalability, Data Engineering, Cloud Computing, Real time Data Processing, AI Workloads

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