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The Machine Room

Schneider Electric

The Machine Room is a brand-new podcast series from Schneider Electric, exploring the challenges and trends facing the future of the global digital infrastructure industry. ​​

Led by Schneider Electric’s SVP and CMO for the Data Center business, Kevin Brown, hear senior leaders from key industry players for conversations that share insights into the heart of data centers and AI infrastructure - exploring the future of energy technology, and the power of digital innovation.

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  • 6 episodes
  • fortnightly
  • Avg 18 min
  • English

Episodes 6

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  • S1 · E4
    Tuesday · 19 min

    Behind the Meter: Powering AI at Gigawatt Scale

    AI infrastructure is increasing electricity demand at a speed and scale few industries have experienced before. In this episode, Kevin Brown speaks with Mandar Pandit, Chief Strategy and Growth Officer for Data Centers at GE Vernova, about how the energy sector is responding as individual data center campuses begin to require as much power as a small city. Mandar explains why limited grid capacity and lengthy interconnection timelines are leading more operators to consider behind-the-meter generation. By producing power on site, data centre developers can take greater control of their deployment schedules. However, this also means assuming responsibilities traditionally managed by utilities, from power generation and protection systems to grid stability and overall energy management. The conversation also explores the technologies that could support this growth more sustainably, including hydrogen-capable gas turbines, carbon capture and small modular nuclear reactors. Rather than viewing AI solely as a threat to the electricity system, Mandar argues that it is exposing existing weaknesses, accelerating innovation and encouraging data centre operators, utilities and technology providers to collaborate in new ways. Featured guest: Mandar Pandit, Chief Strategy and Growth Officer for Data Centers, GE Vernova Key quote: “The AI boom is highlighting the weaknesses in the system and showing us where, as an industry, we need to focus quickly.” Key takeaways: AI data center campuses are increasingly requesting hundreds of megawatts or more than one gigawatt of power at a single location. Grid infrastructure and data center development operate on very different timelines, creating an urgent need for alternative power strategies. Behind-the-meter generation can help operators gain faster access to power by producing electricity on site. Operating behind the meter is not a simple solution, as data centre operators must also manage protection, control, stability and other utility-like responsibilities. Gas generation, hydrogen, carbon capture and small modular nuclear reactors could all contribute to a more diverse power mix for AI infrastructure. Growing data centre demand is stress-testing the energy system, exposing weaknesses and accelerating investment, collaboration and innovation. Follow or subscribe to The Machine Room on your preferred podcast platform for more conversations with the people building the energy and infrastructure systems behind AI.

  • S1 · E5
    September 1 · 22 min

    Finding a Home for AI: From Use Case to Infrastructure

    Enterprise AI has moved rapidly from experimentation to implementation, but turning an idea into a secure, scalable and commercially viable solution remains complex. In this episode, Kevin Brown speaks with Chris Campbell, Senior Director, AI Solutions at World Wide Technology, about how organisations can identify valuable AI use cases, prepare their data and determine where their workloads should run. Chris shares lessons from WWT’s own AI adoption journey, including its evaluation of approximately 70 initial use cases and the development of tools designed to improve internal efficiency. He explains why successful AI projects require more than access to a model or computing power. Organisations also need strong executive sponsorship, clearly defined business outcomes, reliable data and an infrastructure strategy aligned with the needs of each workload. The conversation then turns to hybrid AI infrastructure and the growing role of neocloud providers. Chris explores the trade-offs between public cloud, private infrastructure, colocation and rented GPU capacity, as well as how neoclouds can provide a bridge while enterprises develop their longer-term facilities. With significant new data centre capacity under construction, he argues that the industry is still at the beginning of a much longer transformation. Featured guest: Chris Campbell, Senior Director, AI Solutions, World Wide Technology Key quote: “We’re in the first mile of a marathon that’s never going to end.” Key takeaways: Successful enterprise AI programmes begin with clearly defined business problems and measurable outcomes, rather than technology alone. A cross-functional AI centre of excellence can help organisations assess use cases, data readiness, risk and potential return. Clean, accessible and well-governed data remains fundamental to moving AI projects from pilot to production. AI workload placement should reflect factors such as security, data sovereignty, cost, performance, scalability and time to deployment. Neocloud providers give organisations access to dedicated GPU capacity without requiring them to build and operate infrastructure immediately. A hybrid approach can allow enterprises to use rented capacity as a bridge while developing longer-term private, hosted or on-premises AI environments. Follow or subscribe to The Machine Room on your preferred podcast platform for more conversations with the people turning AI ambition into operational infrastructure.

  • S1 · E3
    August 18 · 22 min

    Powering AI Faster: Turning Data Centers into Grid Assets

    As AI drives unprecedented demand for computing capacity, data centres are becoming larger, denser and more concentrated than anything the electricity grid has previously been designed to serve. In this episode, Kevin Brown speaks with Anuja Ratnayake, Emerging Technology Executive and DCFlex Lead at EPRI, about the growing gap between the speed at which AI infrastructure needs power and the time required to expand the grid. Anuja explains how flexibility could help close that gap. Rather than treating data centres as conventional demand-response participants, EPRI’s DCFlex initiative is exploring how they could connect through more flexible service agreements and operate as responsive grid resources. This could allow new facilities to access power sooner while longer-term transmission and generation upgrades are completed. The conversation also explores the collaboration required to make this possible. Utilities, data centre operators, technology providers, regulators and grid organisations need a common understanding of what flexibility means and how it can be delivered without compromising performance, reliability or affordability. While significant technical and operational questions remain, Anuja believes the industry has the innovation, motivation and partnerships needed to address this once-in-a-generation challenge. Featured guest: Anuja Ratnayake, Emerging Technology Executive and DCFlex Lead, EPRI Key quote: “The fundamental economic driver is not about making the marginal revenue in an hour. It’s about the opportunity cost of not having access, period.” Key takeaways: AI data centers can represent loads of hundreds of megawatts or even gigawatts at a single grid connection point. Providing firm, continuous power to facilities of this scale can require major transmission upgrades and significantly longer connection timelines. Flexible or non-firm grid connections could help data centres access power sooner while wider infrastructure is developed. The commercial value of flexibility comes primarily from accelerating time to power, rather than earning traditional demand-response payments. Data centers can use a combination of computing workloads, auxiliary systems, energy storage and on-site generation to respond to grid requirements. Collaboration across the data centre and electricity industries will be essential to protect grid reliability and affordability while supporting AI growth. Follow or subscribe to The Machine Room on your preferred podcast platform for more conversations with the people solving the power, cooling and infrastructure challenges behind AI.

  • August 4 · 21 min

    Building at the Speed of AI: Inside TeraWulf’s Lake Mariner Expansion (Part 2)

    In the second part of Kevin Brown’s conversation with Nazar Khan, Co-Founder and Chief Technology Officer at TeraWulf, they explore how the company has scaled its Lake Mariner campus from a two-megawatt pilot project into one of North America’s largest AI and high-performance computing developments. Nazar explains why TeraWulf chose to invest in infrastructure before securing its first customer, beginning with a small proof of concept before progressing to increasingly larger data centre buildings. By demonstrating that it could design, construct and operate the infrastructure in practice, the company was able to build confidence among customers, lenders, technology providers and other partners. The conversation also examines what it takes to deliver AI infrastructure at speed. From securing billions of dollars in financing and forecasting equipment requirements to coordinating utilities, suppliers, contractors, customers and local authorities, Nazar highlights the importance of collaboration across the entire ecosystem. He also reflects on Lake Mariner’s impact on the surrounding community, transforming a former coal-fired power station into a growing digital infrastructure campus supporting hundreds of permanent roles and approximately 1,600 construction workers. Featured guest: Nazar Khan, Co-Founder and Chief Technology Officer, TeraWulf Key quote: “The best way to convince someone that you can actually get it done is to go get it done.” Key takeaways: TeraWulf began with a two-megawatt pilot project to develop the skills, designs and partnerships needed to build AI infrastructure. Investing in infrastructure before securing a customer helped the company demonstrate its capabilities and build market confidence. Access to capital is essential, as AI-ready data centres can require investment of approximately $9 million to $10 million per megawatt before IT hardware is installed. Delivering infrastructure quickly requires close coordination between customers, utilities, finance teams, equipment providers, contractors and local authorities. Flexible design decisions and a willingness to evaluate trade-offs can help projects overcome equipment availability and supply-chain constraints. The redevelopment of Lake Mariner shows how former industrial and power generation sites can support new employment and become part of the AI economy. Follow or subscribe to The Machine Room on your preferred podcast platform for more conversations with the people building the power, cooling and digital infrastructure behind AI.

  • S1 · E1
    July 21 · 23 min

    Power First: TeraWulf’s Evolution into AI Infrastructure (Part 1)

    In the first part of this two-part conversation, host Kevin Brown sits down with Nazar Khan, Co-Founder and Chief Technology Officer at TeraWulf, to explore the company’s evolution from power generation to Bitcoin mining and, ultimately, large-scale infrastructure for AI and high-performance computing. Nazar traces TeraWulf’s origins back to Beowulf, where its team spent more than 25 years developing, owning, and operating power generation assets. He explains how this energy expertise allowed the company to move from supplying electricity to managing flexible demand through Bitcoin mining. Rather than viewing each step as a pivot, Nazar describes the journey as a natural expansion of the same core capabilities: finding power at scale, understanding the grid, and building complex infrastructure quickly and efficiently. The conversation also examines why access to power has become one of the defining considerations for AI data center development. From the relative challenges of moving electricity and data to the redevelopment of a former power station at TeraWulf’s Lake Mariner campus, Kevin and Nazar explore how existing energy assets can be repurposed to support the next generation of digital infrastructure. Featured guest: Nazar Khan, Co-Founder and Chief Technology Officer, TeraWulf Key quote: “Generally, I would argue that it’s a lot easier to move data than it is power.” Key takeaways: TeraWulf’s foundations lie in more than 25 years of power generation, infrastructure development, and plant operations. Bitcoin mining provided a flexible source of electricity demand that could respond quickly to changing grid conditions and power prices. TeraWulf views its move into AI and high-performance computing as an evolution of its energy infrastructure expertise, rather than a complete change in direction. Power availability, scale, and speed to energisation are becoming critical factors in the development of AI data centers. Although network connectivity remains essential, data can often be transported more easily than large quantities of electricity. The Lake Mariner campus demonstrates how former power generation sites and existing high-voltage infrastructure can be repurposed for digital infrastructure. Follow or subscribe to The Machine Room on your preferred podcast platform so you do not miss Part 2 of Kevin and Nazar’s conversation, or future episodes exploring the people, technologies, and infrastructure behind AI.

  • July 13 · 2 min

    Welcome to The Machine Room

    In this trailer episode, Kevin Brown, Senior Vice President and Chief Marketing Officer for Schneider Electric’s Data Center Business, introduces The Machine Room, a new podcast exploring the people, technologies and companies building the physical infrastructurebehind AI. ​ ​ Drawing on more than 30 years of industry experience, Kevin explains how the series will go beyond the headlines to examine the realities of powering, cooling and operating data centres, with guests from AIoperators, energy businesses, industry organisations and global technology providers sharing the opportunities and challenges shaping the digital future.​ Key Quote “We’re getting behind the noise to hear the stories of the people building big tech and shaping its future.” Key Takeaways AI depends on physical infrastructure, particularly reliable power and advanced cooling. The Machine Room will take listeners behind the headlines and into the realities of building AI infrastructure. The series will bring together perspectives from data centre operators, energy companies, industry associations, and technology providers. Conversations will explore both the opportunities and the difficult challenges facing the sector. Topics will include energy, efficiency, cooling, resilience, and water consumption. Listeners will hear directly from the people and organisations shaping the future of data centres and AI. Follow and subscribe to The Machine Room on your preferred podcast platform to hear new conversations from the people building the infrastructure behind AI.

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