Uploaded June 2026 | Updated September 2026, 1 week ago
AI models are evolving faster than ever. But as models grow, so does the pressure on the infrastructure behind them.
For AI teams, storage isn't just where data lives—it's what determines how quickly researchers can experiment, train, and ship new models.
Join Sidharth Bajaj and Venkatraghavan Srinivasa from Meta as they share how Meta evolved its storage architecture to tackle two of AI's biggest infrastructure challenges: maximizing GPU utilization and accelerating research velocity.
Learn how storage systems are being redesigned for the next generation of AI at scale at Systems & Reliability in Bellevue, WA.
Register today at atscaleconference.com
AI models are evolving faster than ever. But as models grow, so does the pressure on the infrastructure behind them.
For AI teams, storage isn't just where data lives—it's what determines how quickly researchers can experiment, train, and ship new models.
Join Sidharth Bajaj and Venkatraghavan Srinivasa from Meta as they share how Meta evolved its storage architecture to tackle two of AI's biggest infrastructure challenges: maximizing GPU utilization and accelerating research velocity.
Learn how storage systems are being redesigned for the next generation of AI at scale at Systems & Reliability in Bellevue, WA.
Register today at atscaleconference.com
