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Assessing AI Workloads: How to Choose the Right Environment for Enterprise AI
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Where should your AI workloads run? It's one of the most overlooked questions in AI strategy. From surprising constraints around power, cooling and floor space, to the growing demand for GPU-as-a-Service models, this episode delivers a field-level view of the challenges enterprises face when moving from AI proof of concept to production. You’ll hear why infrastructure readiness assessments are essential, how AI workloads differ from traditional IT, and what to consider before buying that next GPU cluster.
Chapters
1. AI's Growing Power Demands (00:00:00)
2. The Iron Triangle: Power, Space, Cooling (00:06:35)
3. Understanding AI Workloads (00:10:19)
4. Deployment Options: On-Prem, Colo, Cloud (00:16:10)
5. GPU as a Service Evolution (00:23:26)
6. Operational Realities and Challenges (00:31:09)
7. Strategic Planning vs. Reactive Decisions (00:42:28)
8. Key Takeaways and Closing Thoughts (00:45:20)
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