NVIDIA AI Podcast

Episode: GTC Live Washington, D.C. - Chapter 3: AI Infrastructure Ecosystem
Date: November 11, 2025
Host: Brad (NVIDIA)
Guests:

• Gio Albertazzi, CEO, Vertiv
• Olivier Blum, CEO, Schneider Electric
• Krishna Janalagogada, CTO, GE Vernova
• Chase Lockmiller, Co-founder & CEO, Crusoe

Episode Overview

This special GTC edition of the NVIDIA AI Podcast delves into the emerging "AI infrastructure ecosystem" — the foundational power, cooling, grid, and data center systems powering America’s (and the world’s) AI transformation. Host Brad moderates a lively panel with leading executives in energy, infrastructure, and AI data center construction. The conversation moves from urgent scaling challenges to innovation partnerships, highlighting how cross-sector collaboration is enabling the rapid buildout of infrastructure underpinning AI-driven economic and industrial change.

Key Discussion Points & Insights

The Scope of the AI Infrastructure Challenge

[02:23] Gio Albertazzi (Vertiv)

• The explosion of AI and data center investments is leading to an unprecedented need for power and cooling infrastructure.
• Building at industrial scale is necessary: “We will never be able to scale AI at the speed that we have seen…without scaling [power and thermal infrastructure] to absolutely unprecedented industrial proportions.”
• The industry is at an inflection point, requiring new, scalable, and less labor-intensive construction methods.

Memorable Quote:
“We are at a very important inflection moment in this juncture.”
— Gio Albertazzi [02:23]

Efficiency as a Core Lever, Not Just Expansion

[03:57] Olivier Blum (Schneider Electric)

• Efficiency is just as important as raw expansion: “AI depends on compute, compute depends on energy, and energy availability and efficiency depends on AI.”
• Newer AI-driven technologies (digital twins, simulation tools) help optimize every phase from design to operation, making the whole AI factory lifecycle more efficient.

Memorable Quote:
“The type of technology you have now through AI helps you to make energy more efficient…we are excited to leverage AI to make our overall industry more efficient.”
— Olivier Blum [04:09]

The Power Generation Bottleneck and Multi-Source Approach

[05:16] Krishna Janalagogada (GE Vernova)

• Demand for power (for AI/data centers) is soaring: For the past 20 years, US power demand was almost flat; in the next 20, it’s expected to grow 50%, a third from data centers.

• “Energy abundance is really an all of the above kind of answer right now.” Solutions include quadrupling gas turbine capacity, SMR nuclear, wind, solar, and future-proofing with hydrogen.

• The grid is now a bottleneck—transmitting newly generated power efficiently is as big a challenge as generating it.

Notable Statistic:
“Demand is massive. We are sold out through ‘28, maybe through ‘29…quadrupling our capacity of number of gas turbines delivered by 2028 compared to 2020.”
— Krishna Janalagogada [05:41]

The Rise of the “AI Factory” & Extreme Co-Design

[08:15] Chase Lockmiller (Crusoe)

• The data center is evolving into a single, complex AI factory integrating power, cooling, storage, and silicon.
• Extreme co-design with partners like NVIDIA rewrites the rules, e.g., shifting to 800V architectures for dramatic efficiency gains, or modular, system-level design versus piecemeal scaling.

Memorable Quote:
“The process of taking electrons and turning them into tokens is just one of humanity’s greatest opportunities and challenges over the next decade.”
— Chase Lockmiller [08:50]

Modularization & System-Level Thinking

[11:12] Gio Albertazzi / [12:39] Brad

• “Think systems, not just components.”
• Data centers are being reimagined from individual hardware pieces to modular, prefabricated, and integrally designed systems (e.g., VertivOne Core).
• The next few years will see faster, more radical change in data center construction and operation.

The Role of Policy & National Urgency

[12:39] Brad / [13:45] Olivier Blum

• The US is moving quickly, but China’s speed and scale set a high bar.
• Leadership and government are now treating AI infrastructure as a national security issue, aiming to cut red tape and accelerate buildout.
• There’s a shift to collaborative “ecosystem” models—gov’t, large incumbents, and startups working hand-in-hand.

Memorable Quote:
“I think more has happened in the past two years than in the past 32.”
— Olivier Blum (on the speed of current change) [13:45]

The Vital Role of Startups & Flexible Innovation

[16:05] Krishna Janalagogada / [18:22] Panel

• Startups are crucial for hardware and software innovation (grid management, power electronics, real-time software intelligence for grid balancing).
• Large companies like GE Vernova and Schneider Electric are opening up to startup collaboration, fostering a dynamic, open innovation ecosystem.
• The next generation of data centers involves not just hardware but also software and AI-driven operating frameworks.

Memorable Quote:
“There needs to be a base of startups, inventors, creative minds, engineers out there that define what the new technology will be.”
— Gio Albertazzi [19:27]

Data Center Innovation: Power, Cooling, and Software

[20:44] Chase Lockmiller

• Data center power densities are skyrocketing: from 2–4kW/rack twenty years ago to 130–140kW/rack, soon up to 1MW racks.
• Innovations are needed across cooling architecture, networking, and systems software.
• Operating the “AI factory” efficiently is as much a software challenge (data movement, memory optimization) as it is hardware.

Notable Statistic:
“These are 1 megawatt racks. That’s a thousand homes’ worth of power in a single rack.”
— Chase Lockmiller [20:56]

The NVIDIA Ecosystem: Unique, Systemic Innovation

[23:02] Brad & Panel

• Panelists discuss deep partnerships with NVIDIA on:

  • 800V DC architectures
  • Liquid cooling transitions
  • Reference design for gigawatt-scale AI factories
  • Software stack innovations (e.g., Lepton, Dynamo for memory & inference efficiency)
  • Powergen and grid management whitepapers/reference architectures

• Unlike other chip companies, NVIDIA unifies a vast ecosystem, leveraging both its own 35,000+ headcount and a global network of partners/startups.

Memorable Quote:
“NVIDIA…has helped unlock this collective intelligence of society, and the startup ecosystem to big enterprises.”
— Chase Lockmiller [26:19]

Systems-level Challenges: Power Swings and Grid Dynamics

[30:19] Chase Lockmiller

• Gigawatt-scale “AI factory” data centers create rapid, large power swings ("load oscillations")—a challenge for onsite generation and utilities.
• System-wide partnerships (utilities, battery storage, software for load smoothing) are key to solving these new problems.

The Scale of the Opportunity

[31:48] Brad

• The private sector is investing at a scale 10x the adjusted cost of the Manhattan Project over five years ($4 trillion).
• The decentralized, coordinated approach led by NVIDIA is unlike anything seen globally.

Memorable Quote:
“Jensen has said we’re going to spend $4 trillion over the next five years…the speed of that is…commensurate with the Manhattan Project.”
— Brad [31:48]

Timeline of Important Segments

• 00:48–01:11 — Framing AI’s transformation of the US economy, the data center as the “new factory”
• 02:23–03:32 — The power/cooling scaling inflection point (Gio Albertazzi)
• 03:57–05:16 — Leveraging AI for energy efficiency, automation, and digital twins (Olivier Blum)
• 05:16–08:15 — Multi-type power/gen + grid bottlenecks; emergence of energy “abundance” via all tech (Krishna Janalagogada)
• 08:15–12:39 — Extreme co-design, 800V architecture, modularization, “AI factory” evolution (Chase Lockmiller, Gio Albertazzi)
• 13:45–15:23 — Ecosystem collaboration with government to accelerate, national security stakes (Olivier Blum)
• 16:05–19:27 — Startups driving innovation in hardware/software, grid, and efficiency (Krishna Janalagogada, Olivier Blum, Gio Albertazzi)
• 20:44–23:02 — Data center tech leaps: 1MW racks, software-defined efficiency, new cooling/networking (Chase Lockmiller)
• 23:02–30:19 — NVIDIA’s flywheel: Partnership examples, unique ecosystem, software/hardware co-innovation (Panel)
• 30:19–32:50 — System integration challenges (power swings, utility interfacing); historic scale and coordination (Chase Lockmiller, Brad)

Notable Quotes by Timestamps

• “We are at a very important inflection moment in this juncture.”
  — Gio Albertazzi [02:23]

• “The type of technology you have now through AI helps you to make energy more efficient…”
  — Olivier Blum [04:09]

• “Energy abundance is really an all of the above kind of answer right now. Right.”
  — Krishna Janalagogada [06:54]

• “The process of taking electrons and turning them into tokens is just one of humanity’s greatest opportunities and challenges over the next decade.”
  — Chase Lockmiller [08:50]

• “You have to be an innovator and scale. Innovation happens organically [and] inorganically. There needs to be a base of startups, inventors, creative minds, engineers out there that define what the new technology will be.”
  — Gio Albertazzi [19:27]

• “These are 1 megawatt racks. That’s a thousand homes’ worth of power in a single rack.”
  — Chase Lockmiller [20:56]

• “NVIDIA…has helped unlock this collective intelligence of society, and the startup ecosystem to big enterprises.”
  — Chase Lockmiller [26:19]

• “Jensen has said we’re going to spend $4 trillion over the next five years…Private industry is going to spend 10x what we spent on the Manhattan Project.”
  — Brad [31:48]

Closing Takeaways

• AI infrastructure is now central to economic and national security; the US is scaling rapidly but must coordinate (public/private) to keep pace globally.
• Efficiency and sustainability are as vital as expansion; AI is both a driver and enabler of this transformation.
• Innovation depends on collaboration—from startups to hyperscalers, across all layers (hardware, grid, software, cooling) and functions.
• NVIDIA’s ecosystem-centric approach is uniquely catalyzing progress, pushing both technological and organizational speed.
• We are at the dawn of a new industrial revolution, where the “AI Factory” reshapes not just computation but the entire chain of infrastructure — from electrons, to racks, to algorithms, to economic output.

For more on this topic and related episodes, visit NVIDIA AI Podcast.