AI Factory - Enabling Scalable Innovation & Intelligent Systems
summary
Claims that large‑scale training now requires liquid cooling and that inference workloads can often run on smaller air‑cooled systems; recommends containerized interim data centers to retrofit legacy HPC basements fast; cites NVIDIA DGX family and 6U form‑factor challenges, and a DGX developer release for smaller teams; gives a Swiss case (Lightly) as a concrete ROI example and notes industry pressure after announcements like Nestlé’s 16,000 layoffs driving urgent production use cases.
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chapters (7)
- 0:00AI Factory introduction
- 5:13AI-ready data centers
- 18:59AI training to inference shift
- 23:15Europe's AI infrastructure gap
- 26:06On-premises AI challenges
- 29:56AI investment trends
- 39:29Closing & Q&A
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