NVIDIA Keynote: The AI factory Becomes a Balance-sheet Question
On a slide near the start of his GTC keynote last month, Jensen Huang sketched five rectangles stacked on top…
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Build AI for What’s Next, Not What’s First: Avoid the Stop‑Start Cycle
Your AI foundation should be designed for your fourth use case, not your first An AI team builds a promising…
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AI Infrastructure Reality Check: Fix the Network Bottleneck.
Most enterprises plug expensive GPUs into networks built for office traffic. A company invests in high-end GPUs. Racks them. Connects…
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News update: The MDCS.ai x Cisco Podcast is live!
In this podcast, we examine AI infrastructure from an enterprise perspective. Guests with backgrounds in enterprise IT, cloud architecture, security,…
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AI Ecosystem as a brain: The reason most AI pilots never reach production has nothing to do with technology
A large organization launches over a hundred AI initiatives across departments. The first week, enthusiasm is high. People try new…
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Purpose-built Regional AI Factories: Where infrastructure enables an ecosystem
Where infrastructure enables an ecosystem In 2020, while many countries were still debating national AI strategies, Linköping built. In that…
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Your AI Models Are Ready to Scale. Your Cost Model Isn’t.
Six months of work. The AI model performs, the pilot delivers, and the team is ready to scale. Then the…
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From one server to company-wide AI. They own every layer.
How a packaging company built AI infrastructure without the cloud. Trivium Packaging makes cans. Aerosol cans, food cans, metal packaging…
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Your GPUs scale. Your integrations don’t.
Why AI infrastructure breaks at the connections, not the components. Your AI team added more GPUs last quarter. The models…
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Why your AI Stack is a Black Box (even with all that logging)
The logs say everything is fine Your dashboards show green lights across the board. Operational metrics update continuously. Alerts are…
