How to Architect a Scalable AI Tech Stack

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A comprehensive guide to AI tech stacks, covering data infrastructure, machine learning frameworks, MLOps, and Generative AI development.
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This article provides an overview of the modern AI tech stack, breaking it down into data, model, and application layers. It explores the infrastructure required to build, deploy, and maintain AI systems, with particular attention to Generative AI, vector databases, MLOps tooling, model serving, and cloud-native architectures. The guide also examines emerging trends such as multimodal AI, edge deployment, AutoML, and responsible AI practices.