Data / Provocative

๐€๐ˆ ๐…๐š๐œ๐ญ๐จ๐ซ๐ข๐ž๐ฌ ๐Ÿ๐จ๐ซ ๐€๐ˆ ๐–๐จ๐ซ๐ค๐Ÿ๐ฅ๐จ๐ฐ๐ฌ: ๐‘๐ž๐Ÿ๐ฅ๐ž๐œ๐ญ๐ข๐จ๐ง๐ฌ ๐Ÿ๐ซ๐จ๐ฆ ๐๐•๐ˆ๐ƒ๐ˆ๐€ ๐‡๐ž๐š๐๐ช๐ฎ๐š๐ซ๐ญ๐ž๐ซ๐ฌโœ…Yesterday I had the honor of being invited into a small, working brainstorm session at NVIDIA headquarters โ€” an intentionally elite gathering of leadership from NVIDIA, Red Hat, HPE, and Vertiv, hosted by Ingram Micro, convened to think together about what it takes to build the AI Factory of the future. My thanks to Ingram Micro  and Nvidia for hosting and for including me among this group.

Each organization brought a distinct layer to the discussion:

๐Ÿ‘‰ ๐๐•๐ˆ๐ƒ๐ˆ๐€ โ€” the compute foundation, and a GTM model increasingly built through OEM partners rather than around them.

๐Ÿ‘‰ ๐‘๐ž๐ ๐‡๐š๐ญ โ€” the open, hybrid software platform that moves AI workloads from pilot to production across on-prem, cloud, and edge.

๐Ÿ‘‰ ๐‡๐๐„ โ€” the infrastructure backbone: compute, storage, and networking purpose-built for AI at scale.

๐Ÿ‘‰ ๐•๐ž๐ซ๐ญ๐ข๐ฏ โ€” the physical constraints that determine deployability: power, cooling, and data center design.

Ingram Micro โ€” architecting the distribution and enablement model that brings this ecosystem to the mid-market and enterprise customers who need AI Factories but can't assemble one alone.

๐“๐ก๐ž ๐ญ๐ก๐ซ๐จ๐ฎ๐ ๐ก๐ฅ๐ข๐ง๐ž: no single vendor can deliver an AI Factory alone. The winners will be organizations that architect GTM built for interdependency, not exclusivity.

A core concept underneath the discussion was AI Factory economics โ€” total cost of ownership. NVIDIA's own research reframes TCO around cost per token, not FLOPS per dollar, because it measures manufactured intelligence rather than raw compute. That shift changes the calculus of build or buy. Every organization now has to run that analysis explicitly, and getting it wrong is expensive either way.

This is where AIEco (aiecopartners.com) fits. Build-or-buy can't be decided on infrastructure pricing alone โ€” it depends on whether the workflows are worth automating, whether the infrastructure supports them, and whether the workforce is ready to adopt them. AIEco's assessment evaluates all three โ€” Workflows, Infrastructure, Human Adoption โ€” and synthesizes them into a financially quantified, defensible ROI roadmap, giving leaders a validated basis for that decision.

Grateful for the caliber of thinking in the room.Craig Weinstein Marty Battaglia John McNelly Oni Ononye Jarrod G. Chris Renter Erik Eeg Dale Brown Kristofer Holt Tom Enzweiler Joe McKinney Chris Martin Yudy Vinograd Michael Deuschle

#AIFactories

#AIInfrastructure

#NVIDIA

#RedHat

#HPE

#Vertiv

#IngramMicro

#GenAI

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The AI Gap Series โ€” Part 2