The Data Center Frontier Show

In general pros and bullet points, how would you summarize what’s important in this podcast.

This podcast will explore why air cooling continues to matter as liquid cooling becomes more common in AI and high-density data center environments. The goal is not to position air cooling and liquid cooling as competing technologies, but to explain how they increasingly work together as part of a broader thermal management strategy.

Liquid cooling is receiving significant attention because of the growth of AI workloads and higher rack densities. It can be highly effective at removing heat directly from high-performance processors, especially in applications where traditional air cooling may no longer be sufficient on its own. However, liquid cooling does not necessarily eliminate the need for airflow elsewhere in the facility.

Important points for the conversation include:

Air and liquid cooling will increasingly coexist. Many data centers will operate in hybrid environments where high-density AI racks use liquid cooling while lower-density servers, storage, networking equipment, power electronics, and other infrastructure continue to rely on air.

Liquid cooling does not remove every thermal load. Even when heat is captured directly from processors, other components may still generate heat that needs to be managed through air movement. Residual heat within and around racks can also remain part of the thermal equation.

The transition to liquid cooling will often be gradual. Most operators are not replacing an entire facility at once. Existing air-cooled equipment may continue operating for years while new liquid-cooled systems are added. This creates mixed environments that require careful coordination between air and liquid cooling systems.

Heat still has to go somewhere. Liquid cooling captures and transports heat, but that heat still has to be rejected from the facility. Fans and air-moving equipment can continue to play an important role in heat rejection and auxiliary cooling systems.

System-level efficiency matters more than focusing on one technology. Cooling performance depends on how air movement, liquid loops, controls, heat rejection, and other components work together. A highly efficient component does not automatically create an efficient overall cooling system.

Airflow should not become an afterthought. If liquid cooling is added without properly considering airflow, operators can still experience unnecessary energy use, poor thermal distribution, or reduced overall system performance.

Modern air movement is becoming more intelligent. Advances in fan efficiency, variable-speed operation, controls, sensors, and digital connectivity allow airflow to respond more closely to actual cooling demand. This can help reduce energy use while maintaining reliable operating conditions.

Environmental impact should be evaluated at the full-system level. The conversation should avoid broad claims that one cooling method is automatically more sustainable than another. Operators should consider water use, energy consumption, climate, system efficiency, heat rejection, and operating conditions when evaluating cooling strategies.

Air-cooled data centers can still be viable. Not every facility or workload requires liquid cooling. Depending on rack density, equipment, climate, and system design, air cooling may still be capable of meeting performance and efficiency requirements.

Flexibility will be increasingly important. AI workloads, rack densities, and equipment designs are changing quickly. Data centers that can adapt their cooling architecture over time will be better positioned to support future requirements without unnecessary redesign.

The podcast should help listeners understand that the future of data center cooling is not simply a move from air to liquid. In many cases, the more realistic future is a combination of both.

The key takeaway should be that cooling strategy needs to be based on the actual thermal requirements of the facility. Liquid cooling will play an increasingly important role in high-density applications, but efficient and intelligent airflow will continue to support hybrid environments, lower-density equipment, residual heat management, heat rejection, and overall facility performance.

The discussion should remain educational and practical rather than promotional. It should help listeners think about cooling as a complete system and understand where air and liquid technologies each provide value as data center requirements continue to evolve.

Data Center Frontier Show Podcast | DCF Trends Summit 2026

As AI infrastructure expands at unprecedented speed, data center operators face a growing financial and operational challenge: What happens to GPU systems when their first production assignment ends?

In this episode of the Data Center Frontier Show, recorded onsite at DCF Trends Summit 2026 in Northern Virginia, DCF Contributing Editor Doug Black speaks with Linda Li, Chief Strategy Officer of Re-Teck / Li Tong Group, about why GPU lifecycle management must begin at the design and procurement stage—not when equipment is ready for retirement.

Drawing on decades of reverse supply chain experience in telecommunications and electronics, Li explains how rapidly evolving accelerators, increasing power densities, and shifting cooling requirements are changing the economics of AI infrastructure.

The conversation examines four considerations for GPU disposition: remaining operational capability, component-level economics, data security and regulatory compliance, and critical-material recovery. GPUs no longer suited to frontier AI training may retain substantial value for inference, enterprise applications, academic research, or component harvesting.

Li also discusses the importance of continuous asset evaluation, secondary-market timing, secure chains of custody, and designing hardware for second and third operational lives.

The central warning: Companies that fail to establish lifecycle strategies at the executive level risk creating significant amounts of stranded capital as valuable equipment sits idle while market conditions change.

For AI infrastructure operators investing billions in successive generations of compute, the next life of the hardware is becoming as important to financial planning as its first deployment.

Listen to the conversation for a practical examination of how GPU lifecycle planning, circular infrastructure design, and reverse supply chain management are becoming essential disciplines in the AI data center economy.

The conversation around data center power has focused on replacing diesel. But for many hyperscalers and developers, modern standby diesel remains a practical solution amid grid constraints, permitting challenges, and growing reliability demands.

In this discussion, Matt Vincent, Editor in Chief of Data Center Frontier, sits down with Brad Meissner, Director of Product Management at Generac, to explore why diesel continues to play a critical role in data center power strategies—and how low-NOx engines, HVO compatibility, and next-generation emissions controls are redefining diesel technology in 2026.

AI data centers are creating a new kind of power problem. As thousands of GPUs ramp together, fast and synchronized changes in electrical demand can place new pressure on UPS systems, generators and the broader power infrastructure supporting the compute load.

In this episode of the Data Center Frontier Show, DCF Editor in Chief Matt Vincent speaks with Frank DeLattre, President Americas at Musashi Energy Solutions, about how hybrid supercapacitors could help data centers manage those rapid power transients — and why AI may be forcing the industry to rethink the role of energy storage altogether.

DeLattre explains the difference between storing energy and managing power, and why high-power, short-duration storage may become increasingly important as AI infrastructure scales. The discussion explores placing energy storage at multiple points in the power chain, from the UPS to systems closer to the server rack, where transients can potentially be addressed before they propagate upstream.

The conversation also examines whether short-duration storage can help operators get more compute from existing electrical capacity by buffering momentary peaks, as well as the tradeoffs between energy buffering and throttling GPU performance.

DeLattre also raises a provocative question around traditional UPS design: If backup generators can accept load within seconds, how much stored energy does a modern AI data center actually need for ride-through?

The discussion looks ahead to a future in which operators may think less in terms of a single “UPS battery” and more in terms of an energy storage architecture — combining different technologies, durations and locations to solve different power problems across the AI data center.

AI and high-performance computing are changing how data centers are designed and powered. Rack densities have more than doubled in recent years, and power demands continue to climb. For data center operators and engineers, the pressure to scale faster, reconfigure more often, and support higher loads has made the power distribution decisions more important than ever.

This QuickChat video will focus on overhead busway as the optimal power distribution system for modern data center environments. Chris Osian, Product Manager at Starline, will discuss why busway outperforms traditional RPP-based approaches as power densities increase, and what the right power distribution infrastructure needs to deliver: the capacity to support increasing power densities, the flexibility to change without downtime, and the ability to scale with the facility over time. With over 30 years of proven performance in mission-critical environments, Starline is the name data centers have trusted to deliver on all three.