What if the biggest constraint on the AI era isn't compute power, software, or even money, it's how we cool the hardware that runs it all? In this episode, Rob Coyle sits down with Jean-Marc Denis, Chief Product Officer at Submer, to explore why immersion cooling has gone from an exotic idea in a Barcelona garage eleven years ago to what many believe will be the dominant cooling paradigm for AI infrastructure.
Jean-Marc brings nearly 40 years of high-performance computing experience — from designing supercomputers to founding the European Processor Initiative — to a sweeping conversation about intelligence per watt, the power and water constraints reshaping data center strategy, and why the real money in AI is not in training mega-models but in inference at the edge.
This episode covers both the technical and business dimensions of the AI infrastructure buildout, including why the six-month land-to-first-token expectation is forcing a co-design revolution, and how immersion cooling's simplicity — not its complexity — may be its most underrated advantage.
What You'll Learn
Why the AI era has shifted the core efficiency metric from raw compute performance to tokens per watt and intelligence per watt
How immersion cooling's power overhead advantage — from a PUE of 1.3 down to as low as 1.02 — translates to dramatically more compute capacity within the same power envelope
Why power availability, not cost, is now the binding constraint — and how that changes the calculus for data center operators at every scale
The community pushback on large data centers and why immersion cooling's zero water usage is a strategic asset for permitting and local acceptance
The difference between greenfield and brownfield deployments and why investors are now demanding a path from land to first token in six months or less
Why the edge is where the real AI enterprise money is — and why inference at the edge demands a fundamentally different infrastructure philosophy than training at hyperscale
How immersion cooling compares to direct-to-chip liquid cooling in terms of maintenance complexity — and why the comparison has flipped
Submer's co-design approach: turnkey nano, micro, and mini data center solutions from a few kilowatts to 100+ megawatts, designed around usage model first
Why the Cambrian explosion of inference AI engines makes cooling flexibility — not optimization for one chip — the most important infrastructure property going forward
Chapters
0:00 — Introduction — Meet Jean-Marc Denis, CPO of Submer and HPC Pioneer
0:53 — Submer's Story — From Barcelona Garage to Immersion Cooling Mainstream
3:59 — Intelligence Per Watt — How AI Redefined the Efficiency Metric
9:54 — Power Constraints at Scale — What PUE 1.02 Means at 1 Gigawatt
13:26 — Water, Permits, and Community Acceptance — The Hidden Advantage of Waterless Cooling
20:02 — The Maintenance Myth — Why Immersion Is Now Simpler Than Direct-to-Chip
24:24 — Co-Design and the 6-Month Data Center — Land to First Token
28:03 — The Inference Edge Opportunity — Where the Real AI Enterprise Money Is
About the Guest
Jean-Marc Denis
Jean-Marc Denis is the Chief Product Officer at Submer, the Barcelona-based immersion cooling company he joined in November 2024. He brings nearly 40 years of high-performance computing experience, including designing large-scale supercomputers, building an HPC organization from zero to a top-four global ranking, founding and chairing the European Processor Initiative, and launching a microprocessor design company.
About the Open Compute Project
The Open Compute Project (OCP) is a collaborative community committed to redesigning hardware technology to efficiently support the growing demands on compute infrastructure.
