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<p>Many organizations want to leverage open source AI tools—Kubernetes, Kubeflow, PyTorch—but struggle with the operational complexity of managing them at scale. AWS FlexAI initiative bridges this gap by providing a curated approach to running open source AI workloads on AWS infrastructure while preserving flexibility and portability.</p><p>In this 15-minute lightning talk, we'll showcase how AWS container specialists from Korea and ASEAN help enterprises get open source AI to production faster. We'll cover three practical takeaways:</p><ol><li><p><strong>Cost-Efficiency + Flexibility</strong>: Optimizing infrastructure spend without vendor lock-in through Kubernetes and open source tools</p></li><li><p><strong>Real-World Deployment</strong>: A snapshot of how customers in Asia are building production AI platforms on AWS using open source</p></li><li><strong>Hybrid AI Architecture</strong>: Running self-managed open source models alongside AWS managed services (Amazon Bedrock, SageMaker)</li></ol><p>Whether you're adopting open source AI or scaling it across regions, this session offers actionable insights and a practical roadmap.</p><p><strong>Keywords</strong><br>Open Source, AI/ML, Kubernetes, MLOps, Hybrid Cloud, AWS</p>
