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As AI evolves from model training to large-scale inference and agentic AI, storage has become a strategic component of AI infrastructure. Technologies such asKV caching are transforming inference performance by reducing latency, improving throughput, and lowering energy consumption, but they also introduce new demands for scalable, persistent storage beyond local DRAM and SSDs. Join expert speakers as they explore how software-defined storage architectures are enabling the next generation of AI platforms by delivering the performance, scalability, and resilience required for modern AI workloads. Join this episode to explore:

• How software-defined storage supports enterprise AI at scale
• Infrastructure design considerations for persistent KV cache deployments
• Approaches to balancing performance, cost, and energy efficiency
• Deployment examples and architectural best practices