Lambda and Cologix debut NVIDIA HGX B200 AI clusters in Columbus, Ohio

September 9, 2025• 24 min read

AI infrastructure is no longer confined to the coasts. With Lambda’s one-click clusters, Supermicro’s energy-efficient systems, and Cologix’s carrier-dense facilities; Columbus, Ohio has become home to the Midwest’s first NVIDIA HGX B200 powered AI cluster. In this Data Center Frontier's podcast, Lambda’s Ken Patchett - VP, Data center infrastructure, and Cologix’s Bill Bentley - VP of Hyperscale and Cloud Sales, discuss what this deployment means for the future of regional AI infrastructure, why the “aggregated edge” is becoming essential, and how flexible, scalable GPU access is reshaping enterprise AI adoption across industries from healthcare and manufacturing.

Audio Transcript

0:06: Hello and welcome back to the Data Center Frontier show where we explore the evolving digital infrastructure powering tomorrow's world.

0:13: I'm Matt Vincent, editor in chief with Data Center Frontier, and, today we're diving into a story that speaks directly to the rapid decentralization of AI infrastructure.

0:26: And what it means when powerhouse technologies like Nvidia's HGX B200 platform, usually the domain of coastal hyperscale markets start showing up in the heart of the Midwest.

0:39: Well, Cologix, Lambda, and Super Micro have teamed up to launch, Columbus, Ohio's first NVIDIA HGX B200 based AI cluster deployment.

0:50: The project combines Lambda's one click clusters with Super Micro's energy efficient hardware, and Cologix's dense carrier rich scale logic SM facility, call 4.

1:03: There in Columbus, so, welcome in, Bill Bentley, VP of Hyperscale and cloud sales with Cologix's, and Ken Patchett, VP, Data center infrastructure with Lambda.

1:18: thanks a lot for, joining us here on the podcast.

1:36: so in my, the project that I described in the preamble marks the first deployment of NVIDIA HGX B200 clusters in the Columbus, Ohio region.

1:46: just sort of big picture, I'll ask both of you.

1:49: I mean, I think many in our audience know, but, why Columbus and why now, if you can talk about the significance of the, Of the region OK you wanna jump in?

2:02: Yeah, yeah, I'll take that first from the lambda perspective.

2:05: I, I think it's, it's important to understand that the shift to super intelligence is, is happening now.

2:12: Systems that can reason, adapt, and accelerate human progress, right?

2:16: This, this requires an entirely new type of infrastructure.

2:21: It means capital, it means vision, and that means the right partners.

2:25: Columbus with Kologics made sense for us because just beyond being centrally located, they're highly connected, they're cost efficient, they're built to scale, and it's important to understand we're not chasing trends here.

2:37: We're laying groundwork.

2:38: For a future where the intelligence infrastructure is as ubiquitous as electricity, partners like Kologics, we're bringing inviti the HGXB 200 clusters to the Midwest for the first time.

2:49: It's a major milestone for the region and frankly a major milestone for shepherding in the super intelligence age.

3:01: Yeah, so from a facility perspective, Columbus is uniquely situated where it's a rich intersection of long haul fiber, there's tax incentives that are available from the state.

3:11: It's also low-cost utilities that have all catapulted Columbus to one of the top US markets.

3:16: , add to that the increased density of hyper scalers that have deployed their local enterprises, manufacturing, and the Columbus ecosystem is ripe for growth.

3:26: So it's just a natural geography and location for AI workloads that are seeking geographic diversity without sacrificing performance.

3:38: Yeah, I wanted to ask you in terms of this project, does it represent sort of a signal that major AI workloads are, starting to shift away from the traditional coastal hyperscale markets?

3:52: I mean, does, does it change, you know, a, a deployment like this, does it change the economic geography of AI infrastructure in North America to any degree, or how do you characterize it?

4:06: Well, you know, I, I, I love this question because I, I like to think of lambda as an AI hyperscalar.

4:15: so, you know, the, the line between AI workloads and traditional hyperscale are blurred.

4:21: AI workloads are now an integral part of business for traditional hyperscale providers.

4:26: They partner with AI hyper scalers like Lambda, their customers, they jointly support end customers, so it's, it's a new ecosystem for AI.

4:40: So like, what does that mean?

4:44: So Columbus, it's not a tier two market anymore.

4:48: The biggest hyper scalers in the world have been building there for years.

4:51: So we're not abandoning one coast for the other.

4:53: It's really, the workloads are co-mingling across all these regions now, right?

5:01: So like Lambda, an emerging hyperscalar ourselves.

5:04: Our megawatt footprint, we're multiplying by 4 between 2025 and 2026, and it's only getting faster.

5:12: So we're in Texas, Ohio, California, Illinois.

5:15: We're democratizing the AI infrastructure and we got to deliver it where it's needed and where it's needed is where we will bring it.

5:25: definitely, important distinctions and, you know, to, to keep in mind, not to oversimplify.

5:32: so next question is, Cologix describes this, Columbus project as a hyperscale edge, deployment, I believe.

5:41: What, what does a term like that mean in practice, you know, and how is it different from traditional definitions of edge and, and hyperscale?

5:55: You get the best of both worlds. It's scalability, it's network density, it's accessibility to CSTs, service providers, and enterprises for interconnection.

6:05: The Columbus campus is the interconnection hub in the Columbus market.

6:09: It offers a unique ecosystem that directly interconnects our enterprise customers with service providers, whether it's carrier service provider, AI or AI specific workloads like Lambda.

6:20: and then, it's unique in that it sits on our interconnection campus, but it's a wholesale facility so we can support megawatt scale workloads like lambda, and, you know, their customers while still offering our bread and butter interconnection platform so it does it's both hyperscale and edge.

6:42: Yeah, I'll tell you, I tend to call it the aggregated edge like.

6:49: When you're really thinking about this, I've been working this for a while, this aggregated edges where all the workloads happen and they come to a place and 80% of the work needs to happen there.

6:59: Cologix is great in their location for that.

7:02: So this aggregated edge takes most real world AI workloads.

7:10: They don't need the same setup as a frontier model training, right?

7:14: So about 80% of our workload, it happens at that enterprise layer.

7:18: So this kind of deployment, this kind of deployment, it really gives us the space and that we need to handle that work efficiently, which is close to the users and with real-time responsiveness, but still connected to like these large language learning models.

7:32: So that aggregated edge is gonna be a real important move as we start moving forward, and I think that That shift from what we used to call tier 1 and tier 2, it just doesn't exist anymore.

7:46: It's an aggregated edge.

7:59: so lambdas one click clusters.

8:02: We know promise rapid, provisioning and minimal complexity for end users.

8:08: How does this model impact the traditional procurement, integration, and deployment timelines for enterprise AI?

8:21: time to market is the most important thing for anybody in, in this world, and also from the enterprise, the, the ability to leverage and action these really expensive server racks and these, these LLMs that we have out there.

8:35: , from an inference standpoint, it's important to understand that one click cluster, it reduces time to value for the enterprise.

8:44: It used to take weeks, months, like lining up GPUs, getting data center space, provisioning software, configuring the systems.

8:52: We can do this nowadays.

8:53: Lambda has deployed the GPU AI compute platform infrastructure in places like Cologix's, to where a customer can now call up and dial up.

9:04: I need 248, 1634 and just keep doing the multiples, and they can get that in their hands in days now as opposed to months.

9:13: That's one of the most important things that we can really do.

9:17: And, you know, none of the enterprises that we talked to, they don't think they're immune from disruption from, let's say, competitors becoming faster or leaning in and embracing AI.

9:27: They know that they need to move from their proof of concept to their production in record time.

9:32: So at Lambda, we've proven with point the cluster that we can deploy thousands of GPUs very quickly.

9:38: And the new large language learning model deployments were under 90 days, and that's the speed that AI development requires today.

9:44: One click cluster is days, new clusters and new data centers under 90 days.

9:57: Definitely because from a facility standpoint, Lambda's one click clusters change everything.

10:06: We now have a really unique category of customer like Lambda that requires incredible scale scalability from a user perspective.

10:13: So if Lambda has a large one click customer, then Cologix needs to be prepared to scale from 0 to megawatts within seconds, and that is a, a really new dynamic in the industry.

10:24: , and it raises the stakes for operational excellence from the facility management perspective too, so definitely something new that that has, you know, it changed the course of history from a data center perspective over the last few years.

10:38: It's some of the newest and latest and greatest enhancement in human technology in the history of the world.

10:53: And you can't run this in, in a place that is, doesn't have the capability to respond and work in, this kind of speed or with this kind of completeness.

11:06: We have to find the right partners that are building the right data center with the right type of infrastructure that can respond and work with us.

11:21: We're learning where the boundaries on the envelopes are.

11:24: We're uncovering new problems with between facility and electrical usage all the time.

11:30: So it's gonna be, I think it's really important to understand that when we pick the places that we go as cologics, excuse me, as lambda.

11:37: Places like Cologix's, they have a strong facility and good facility engineering background, and they can actually help.

11:45: Solve the problems that are being uncovered by today's scale.

11:48: And at the aggregated edge, that, that problem is gonna be even more manifest cause most buildings historically weren't built to be able to handle shifting electrical workloads that that you see with AI.

12:00: There is a dramatic impact from the use of systems that Supermicro has provided lambda, and we're working hand in hand to change the landscape of data center design with systems like Super Micro and Lambda implementation.

15:09: Well, said briefly, there is a dramatic impact from the use of systems that Supermicro has provided lambda, and we're working hand in hand to change the landscape of data center design with systems like Super Micro and Lambda implementation.

16:20: The industry is, is It's a complete industry transformation.

19:14: Yeah, so Columbus is unique centralized geography. It provides access to the intersection of long haul networks in the Midwest.

20:25: I'm pretty excited about that.

32:10: And we have to do it responsibly, and we have to make this happen.