The rapid, exponential growth in model capabilities and training dataset sizes over the last few years has accelerated AI innovation. New frontier models are now being released in a matter of weeks, down from months just a year ago. This pace makes reliable, consistent fast access to storage essential for managing both the speed and cost of development. This presentation will detail how we evolved Meta’s Storage Architecture to overcome two key hurdles: optimizing GPU Utilization and maximizing Research Velocity.
