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Learn how to simplify AI application development by leveraging Kubernetes to streamline complex Retrieval-Augmented Generation (RAG) pipelines in this 26-minute conference talk. Discover the challenges of building productive language model applications, including the complexity of providing proper context and grounding models with organizational data, and explore why RAG implementation often becomes a significant undertaking involving vector databases, embeddings, and indexing. Understand how KAITO, a CNCF sandbox project, addresses these complexities by enabling developers to quickly build RAG pipelines using the RAGEngine Custom Resource Definition (CRD), reducing the need for complex coding and allowing focus on application logic rather than infrastructure management. Gain insights into practical approaches for making AI application development more approachable and accelerating your development process through Kubernetes-based simplification strategies.
