How Meta Scaled AI Training Storage for the Next Generation of AI @scaleconference
How Meta Scaled AI Training Storage for the Next Generation of AI  @scaleconference
Uploaded June 2026 | Updated September 2026, 1 week ago
What does it take to scale storage infrastructure for AI training at Meta?

Join Sarang Masti and Weiran Liu from Meta as they share how data normalization helped optimize AI training storage at massive scale.

If you're building AI systems, managing data infrastructure, or preparing for growing AI workloads, this is a session you won't want to miss.

🎤 Catch this session at AI & Data on June 15. Register today at atscaleconference.com!
How Meta Scaled AI Training Storage for the Next Generation of AISave The Date - @Scale: Product on Oct 22!Architecting Infrastructure for the AI Native Future: Scaling Autonomous Agents on Google TPUsEnhancing Runtime Reliability in LLM Training via Fine-Grained Observability by Lei ZhangBuilding Storage for AI at ScaleLearn from Zoom’s AI Product Manager, Danran Chen!How Meta is Advancing Flash Storage with High-Density QLC Deployments!Live from SCCC: Fiber Networks Innovations for AI at Scale | Fabrice Ouandji and Sebastian GaultScaling Llama4 Training to 100K - Live from SCCThe Agentic Infrastructure Gap: In-Distribution Languages Make It a Coding Problem | Joe DuffyLightning Talk: AI-Native Network Capacity Management | Mohab Gawish, MetaLive from SCCC: MetaRoCE: From Spec to NIC to Open Source | Balakrishnan Raman and Sandeep Nagaraj
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How Meta Scaled AI Training Storage for the Next Generation of AI

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