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As AI models grow exponentially in scale and complexity, attention has largely focused on accelerating compute and network performance. But is storage becoming the hidden bottleneck? This episode examines whether storage and memory technologies are evolving fast enough to keep pace with the demands of next-generation AI workloads. Join this episode to:

• Explore the growing performance gaps between compute, memory, and storage
• Discover the scaling challenge of transforming data into vectors for training and inference
• Examine the evolving architectures for storage