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AI deployments are increasingly constrained by how effectively racks can utilize available power and cooling capacity. While PUE has long served as the industry's benchmark for energy efficiency, it does not measure how effectively that power is converted into usable compute. This episode explores how improving rack-level Power Compute Effectiveness (PCE) can help operators maximize productive AI compute within existing infrastructure constraints, shifting the focus from measuring consumption to measuring output. Join this session to:
- Learn what limits AI compute growth in modern data centers
- Explore how power and cooling constraints impact capacity
- Learn how to maximize deployable compute within existing envelopes
- Supporting AI environments with next-generation cooling architectures
