AI Inference Zones: CoreSite’s Brian Eichman on the Future of Data

[00:00:00] Brian Eichman: I think it’s going to be a very big cultural shift, and I think it’s imperative that we’re in the age of the machine, that we don’t lose the human aspect of business and interaction and collaboration and all of those things. I think it is critically important. I’ve got three kids. And making sure that they can still make eye contact and pick up the phone and call somebody, shake a hand, those types of cultural norms and things like that, it’s on us right now to preserve those qualities.

[00:00:58] Intro/Outro: Technology has transformed how we live, work, and connect. And behind that change are visionary people with bold ideas. Welcome to the Bridgecast, where host Scott Kinka explores hybrid work, AI, and our evolving future with tech’s brightest minds. Presented by Bridgepointe Technologies, the nation’s leading tech advisory firm. Experience a better way, the Bridgepointe way.

[00:01:28] Scott Kinka: Hi, and welcome to the Bridgecast. Today, I am joined by Brian Eichman. He’s the Vice President of Business Development and Solution Architecture at CoreSite, a leading expert in hybrid IT, cloud ecosystems, and AI infrastructure. He’s also a returning guest. We’ll get into that today. Brian spent over 13 years at CoreSite driving innovation in cloud services, interconnection solutions, and data center technologies. He’s played a pivotal role in enabling enterprises to optimize their IT infrastructure and accelerate digital transformation by leveraging high-performance and low-latency connectivity solutions. His work helps companies unlock the full potential of their hybrid IT strategies, ensuring that they can scale securely and effectively in this rapidly evolving digital landscape. Brian, welcome back to the Bridgecast. How are you?

[00:02:14] Brian Eichman: Thanks for having me, Scott. Amazing job on the intro. Sorry for, uh, so many tongue twisters in there in the description, man. Not intentional.

[00:02:23] Scott Kinka: Hey, listen, all good. AI writes it, doesn’t think about the speakability of it, and then we tweak it. So it’s all good.

[00:02:29] Brian Eichman: Well executed.

[00:02:30] Scott Kinka: We were first together. I think our first episode together aired in November ’23. But for those who maybe didn’t listen to the last 80 episodes to get that one, let’s get reintroduced. Tell us a little bit about you.

[00:02:47] Brian Eichman: Thanks, Scott. Yeah, it was. The time flies. Uh, September ’23 is when we just kind of remember the essence of our last dialogue. So great job to you and the team for having 80 episodes, because I think that was one of your first, but I think I learned it was one of the top podcasts out there with what Bridgepoint is doing. So fantastic work. But just real quick about myself, you really nailed it. I’ve worked at CoreSite for 13 years. We’re one of the leading colocation providers in the U.S. Really, the largest percentage of my career was in engineering. On the back half, I found a good opportunity to pivot a bit in my career, leveraging some of my technical fluency into product development, building up a technical sales organization here at CoreSite, and then really have just focused now more on corporate strategy and making sure that CoreSite is well-positioned to compete now and into the future. So I look forward to the dialogue today.

[00:03:50] Scott Kinka: Fantastic. And for those who maybe aren’t familiar with CoreSite without it turning into a commercial, you know what I mean? Give us the superpower. Tell us a little bit about the company.

[00:03:59] Brian Eichman: Great timing today. This is a really neat milestone in our career that I’ll get to here in just a moment. But really simply put is CoreSite, there’s many data centers out there, but our superpower is really about bringing together a world-class ecosystem inside of the data center. So it makes it really easy for customers to integrate into their digital supply chains, distribute their Internet-facing applications, build those hybrid architectures, and we do that by having a high concentration of on-net carriers in our campus, native cloud on-ramps, and coupling that very uniquely with wholesale high-density data center capacity in a given campus. And the cool thing I was telling you about this is the great day that we just celebrated here at CoreSite. When I started in 2012, we had a revenue of about $150 million annually. Just this last quarter, we broke the billion-dollar mark. So we are now a billion-dollar revenue company, which is just hugely important in our growth, and we couldn’t have done it really without the support of our partners like Bridgepoint.

[00:05:15] Scott Kinka: I appreciate that last statement, and congratulations to you guys. That’s incredible. Where are you calling us from right now?

[00:05:21] Brian Eichman: Yeah, I’m based out of Denver, Colorado.

[00:05:23] Scott Kinka: And, but you guys are all over the U.S., and, uh, you know, people are certainly familiar with the brand. Beyond the tech and infrastructure, we’re going to come back to that in a minute. You’ve been an advocate for the importance of community and collaboration. You’re a volunteer with several organizations like Junior Achievement. I mean, just tell us how that ethos translates into your leadership at CoreSite, especially when it comes to fostering innovation and partnership and all the things that you do. Tell us about that ethos that comes from your charitable work.

[00:05:51] Brian Eichman: Certainly, for myself, I’ve had the great opportunity to pivot several times in my career and reinvent myself. That doesn’t happen alone. I’ve benefited from great mentors, people that opened up windows and doors for me, sometimes kicked me in the rear end to walk through them. You just don’t do this journey alone. You know, you want to make sure that you have great mentors. You pass that along. I think humility and just collaboration are really keys to my success. I’ve just found a lot of value and just joy in passing that along, and it just helps me grow individually, but as a manager, and just really makes me more effective as a leader.

[00:06:39] Scott Kinka: Incredible. Let’s jump right into it then. I read a note, a blog recently. I think you may have been the author from CoreSite about this concept of “inference zones.” I found it really interesting. I mean, I feel like every episode, we’re talking about AI right now, but this concept of inference zones is really interesting. So I’m going to ask you to just cliff-note that for us. In your world, give us the concept of an inference zone as you guys think about it in the CoreSite world.

[00:07:08] Brian Eichman: This really came on the heels of some AI leadership conferences and just thought leadership that I had attended. There’s just a ton of chaos in the market. AI is everywhere. There’s data centers being built everywhere. The machines are going to take over the world. It was just very difficult to kind of put some sense of logic and reasoning to it. And so I just started thinking about what’s happening, where is it happening, and why is it happening that way. And I started thinking about, alright, where are all of these models being trained? Where will they ultimately be served once they move from the education phase, the training phase, into the more inferencing, which is where it gets monetized? AI really becomes production quality. It touches us every day as consumers, and, ultimately, it gets commercialized, if you will. And so I started putting together some leadership here, and I had some really good conversations with our strategic partners, which are the big cloud providers where a lot of this investment is originating from. And what I had learned is that these models get trained, but then they move from where they’re being trained out to the edge, where they will be served and monetized. And there’s going to be these kind of key markets where that’s going to occur. It’s really not a huge secret. It’s going to be distributed and monetized in major edge markets, right? These are major Tier 1 markets, high concentrations of enterprises, high concentrations of consumers, and where all of that meets Internet infrastructure and cloud infrastructure. And so if you just look at how the clouds have distributed their infrastructure, Scott, there are clusters, a concentration of cloud infrastructure, in certain key markets. We know these as Northern California, we know these as Chicago, Illinois area, Northern Virginia, Ashburn, Reston, obviously, and that’s where all of these clouds are going to start interoperating, right? And so that is the kind of genesis of an inference zone, which is where you can plug in over high-speed, low-latency pipes into all of your models, into all of your data streams, and ultimately deliver out real-time inferencing applications.

[00:09:49] Scott Kinka: Got you. And for those not sure if…

[00:09:51] Brian Eichman: That was the cliff notes, by the way. I don’t know if I’ve ever been accused, though.

[00:09:55] Scott Kinka: No, that was really, really good. But I think there’s probably two topics that come out of that. Right? One is more about AI, which I want to just talk about. I’ll talk about that one first so we can set the table. And then the second one really is this idea of kind of embracing an ecosystem in data center strategies going forward, which is a thing. I mean, frankly, we talked about 20 months ago as a stalwart of the way that you guys work. Like, it wasn’t about trying to close off and sell as much space as you possibly can. It was about recognizing that businesses were going to move where the center of their universe is. Right? And hybrid work had a lot to do with that, too. Move where the center of their data universe is. But, ultimately, the orbit and the distribution doesn’t really come out of your, in many ways, particularly around AI, out of the data center, out of your data center. Right? It’s a place where data that has to be inferenced, right, ultimately lives, and proximity is important. So but before we get into that, the importance and proximity, the word “inference” and the idea of kind of learning through making decisions, right, from an AI perspective. Or, I also think “reference” is another good way of looking at it. Like, I give a lot of talks on AI and people are like, the robots are going to take over the world. And I’m like, it’s designed to be referential, not self-referential. Right? Like, at the end of the day, what it is designed to do is put pieces of information together, and that information is in various spaces. And that’s where the power comes in. So I think I maybe gave a little bit of a tease, but when you talk about it in terms of AI models working, can you just explain the concept of inference, if you will, and kind of how it works and why it’s important?

[00:11:25] Brian Eichman: This is such a complicated technology and topic. For me to be able to get some grasp and kind of understanding of it, I have to simplify it down. And I use analogies a lot in how I explain technology. So here’s the one that I’ve come up with for me to kind of get this understanding is, it’s kind of a a reference to how we go to college, higher ed to learn, and then what happens after that. Right? And you go off to college, and this is the training phase of AI. You’re going out, you’re getting exposed to professors’ perspectives. You’re getting formal education out of books. There’s Internet research. There’s, you know, people that are at your college from all over the world, so you’re kind of getting this worldly exposure. That’s the training of the AI, right? You’re paying, if you will, to go gain that knowledge. And that’s kind of where we’ve been. We’ve been paying to train these models out kind of in the middle of nowhere, and we buy expensive GPUs to do it, and we consume just a tremendous amount of power and space. But now we’re shifting into the inference stage. So we’re leaving college now, and we’re taking that knowledge with us from the small college town, and we’re going out to big cities, if you will, to go make good decisions based upon the knowledge that we have trained and ascertained over the last four, six, guys like me, eight years that took forever to finally finish a degree, so we can make real-time decisions. We can now inference, if you will, much faster leveraging what we’ve learned, what we’re still intaking on current, you know, kind of reality, if you will. We’re now inferencing. And I think that’s kind of what we’re looking at now is that we’re moving into the inference phase with these apps. We’re going to start making money on AI. We don’t make money in college. We make money later when we’re able to inference based upon the knowledge we’ve gained, and I really see that’s what’s going on with the models now. It’s time to go make money at them. Companies are coming to market, and they’re going to start monetizing that knowledge and being able to inference on it.

[00:13:41] Scott Kinka: Got it. So to make that inference happen at the speed of the consumer, I’m trying to contextualize this. Hope I get it wrong. Please correct me. The idea here is we’re probably going to be interacting with these models, UIs that may sit in public close to the edge near me as an end user, and then that front end needs a low-latency connection back to a model, back to disparate RAG sources of information to leverage against the model. The idea is we’ve got to be able to get a front end close to the edge, close to the end user with good speed, good access, a predictable way to collect the rest of the data to create inferences around to operate at the speed of the consumer. I mean, I probably oversimplified the hell out of it.

[00:14:23] Brian Eichman: No, I think that’s a perfect way. I think you and I make a good team, right? Because I’ll kind of drag it along and make it a little more complicated. You bring me back down to Earth and make it digestible. Think about one of the leading social media apps. How they’re serving you content that has been curated based upon your views and your likes, your habits, if you will, and they are leveraging AI and inferencing to curate and serve you content based upon your prior decisions.

[00:14:58] Scott Kinka: So what’s the message for the listener there, by the way? Like, not everybody has a product necessarily that right now they’re thinking about how that’s going to be driven via AI. Maybe they just need data center space or, you know, like, contextualize it into some use cases for me, like the one you just gave, if you would. So I’m just sitting at home. I’m listening. I’m in the car. I’m on the treadmill right now, and I’ve got an impending decision potentially to make about a data center or a strategy I want to build over the next couple of years. Give me some of the, like, use cases you’ve seen where these inference zones kind of really matter.

[00:15:28] Brian Eichman: And we are seeing this. This is, you know, not just a thesis. This is rooted in customer deployments and interactions that we’re having. From an industry perspective, financial services is leading the charge for inferencing quant training, specifically. Probably the fastest-growing segment inside of CoreSite is the financial services sector. I would say from there, we’re looking at media and entertainment, specifically gaming, as being a major adopter of this. And then lastly, I would say social media has been another component of that. I think health care is going to start to move in a little bit, but really, finance, gaming, and then social media have been the three.

[00:16:21] Scott Kinka: Super interesting. And then I guess when I think about it from an inference perspective, this isn’t just about data centers or public clouds, right? I mean, this is about network. It’s about edge. It’s about security. And frankly, it’s about work from home. It’s about where workers are. I mean, like, it’s changed very broadly in the last five, six, seven years. That’s a lot to tackle at one time, I think, from an architectural perspective. Like, for some of our listeners who might be thinking about, we’re very used to, like, I’m making a data center decision. I’m making a cloud decision. I’m making a network decision. I’m making a security super-siloed. It feels like we won’t be able to do that anymore, right? Or at least it all needs to be considered at the same time. What kind of advice do you have for IT leaders who are thinking about the next generation? Let’s just take their infrastructure in general. It could be any one of those categories. What’s your advice for them for future-proofing and making sure that if they’re not addressing every decision at the same time, certainly ensuring that they’re not making an isolated, a siloed decision that will later affect their ability to build a malleable infrastructure for the business to support some of the use cases you’re talking about?

[00:17:28] Brian Eichman: Great question. And, you know, what I will say is, first off, I want to validate that they’re doing it much better than they had. IT leaders are being much more comprehensive and taking more of an integrative kind of view of their tech stack and overall IT strategy and how that rolls up into corporate-level strategy. And I think hybrid IT really is what set that foundation is that we’ve been living in this hybrid model. We’ve learned some lessons along the way about being cloud smart, how data center colocation fits into that strategy, and allows us to be very nimble with how we deploy technology and applications. So I think we’ve got a great foundation that we’re starting on, much better than when we spoke 20 months ago. We’ve done some research. One of our major research pieces every year is our State of the Data Center Report. We go out and survey about 300 CIOs about a variety of topics. And hybrid, cloud smart, multi-cloud, right, connectivity, these are core concepts now that are central to their domain now. They’re not new concepts to the CIO. So I do think we’re doing a better job there. But what I would say that lessons to be learned, things to be mindful of and considerate of is, we’ve learned from our past that one strategy is not the ultimate way forward. It is being very diligent about how you deploy your apps, where they are deployed, who they are deployed with, integrating them together, be flexible, choose the best fit, not the best price, and, you know, it’s going to be a comprehensive mix of technologies that’s going to help you solve all of this. Proximity matters. That is a big one.

[00:19:27] Scott Kinka: So reading that back, it’s if you’re making a network decision, make sure it’s got cloud on-ramps. If you’re making a cloud decision, make sure that cloud plays friendly with a data center provider. You’re making a data center decision, make sure that they have an ecosystem surrounding them like you guys do, where you can get to all the places you’ve got to get to low-latency kind of in that. So you’re not going to make all the decisions at one time, but you need to add the consideration of proximity when you’re making any one of these decisions. Frankly, whether it’s network or data center or cloud decisions or a hybrid provider that you’re working with or a bare-metal provider that you’re working with at the end of the day, it’ll serve you well. Is that a reasonable way for me to sum it up?

[00:20:06] Brian Eichman: Always good.

[00:20:07] Scott Kinka: I love it. Alright. Let’s turn it around a little bit. I’m just curious culturally. I love questions about how AI is kind of modifying our relationship with our employees also. In many ways, we’re in the greatest social experiment of all time, or at least since the beginning of the industrial revolution, you know what I mean? Where we paid for hours in hard labor, now we’re paying for hours largely in soft labor, but it’s still like, how many hours is your butt in a seat or online, and that’s how I value you versus an output. And AI is supercharging that. So, like, as you think about all of this that’s happening right now, tell me how we think about kind of the different role of humans, right, and the employee-human relationship in work over the next handful of years, and are our systems prepared for that?

[00:20:56] Brian Eichman: I think it’s going to be a very big cultural shift, and I think it’s imperative that we’re in the age of the machine, that we don’t lose the human aspect of business and interaction and collaboration and all of those things. I think it is critically important. I’ve got three kids. And making sure that they can still make eye contact and pick up the phone and call somebody, shake a hand, those types of cultural norms and things like that, it’s on us right now to preserve those qualities. But, you know, at the same time, I think, to your question is, I think it’s fantastic that we have these tools available. And the smart use of AI to make us more effective and more efficient, that is the intent behind AI and machine augmentation, and it’s sometimes I would have to agonize writing an email or, I think I’ve told you before, I coach. And thinking about, I’ve got to write this weekly email about what practices we’ve got going on and we’ve got these games and make sure Jimmy’s getting the right amount of rest and you’re eating right and blah blah blah. It’s much more efficient for me sometimes to go to AI and say, hey, I need you to draft a letter for me that has this information in it and it’s to some soccer parents and it is brilliant. And it comes out, you’re like, alright, that’s a little too formal. Make it a little more folksy to match kind of how I am, and then it rewrites it in three seconds. And I’m like, right on. I’m going to make six or seven tweaks on that. I’m good to go. I can move on to doing the next thing. So it just makes us much more efficient, but I think it’s on us to use it wisely.

[00:22:45] Scott Kinka: Yeah. I filmed another episode today. I’m not sure if that’s going to drop before this one or this will drop. So I’ll just kind of mention one of the things we went down the road on. We’re having a little bit of an existential crisis around commonality of responses from large language models. So many of the models now have a baseline that’s based off of the OpenAI model, right? Like, even if you’re using it in a RAG format where you’re just using it effectively for inferences, right, against your own data, but you’re not exposing your own data. It’s still using that model. Do you worry about the commonality of responses? Like, over time, the better the model gets to your point, you know, “but can you make it sound like me?” But response number one, are we all going to come out sounding the same way? It’s something I hadn’t heard as a big objection until lately. People are starting to wake up to how these models work.

[00:23:35] Brian Eichman: How do you think about that? That kind of dehumanizes it a little bit and just kind of makes it very, uh, vanilla. So I would—this isn’t my prediction if you ask me one for today, but I do foresee that there will be a new domain or element that can get added into AI as it gets more enhanced and sophisticated that adds some sense of personalization to it, right? I do think it’s like this whole other dimension that I think AI will evolve into that does make it more human-like and not so machine-like. And that’s terrifying that at some point it will become no longer a 3D model, but now we’re talking the fourth dimension, if you will, and that’s like humanesque.

[00:24:29] Scott Kinka: It’s funny. We had a webinar weeks ago, and one of the presenters built an agent on a call in two and a half minutes, right? And he was having some fun with me. He called it the Scott-bot. But if you just think about it from a sourcing perspective, right, like, it’s all about how well you write your prompts and what is it you’re doing. He basically said, like, I need a bot on Scott. What did he turn it to? He turned it to the website where the transcriptions of all of the 80-plus episodes are. So it’s got 80 hours of me content, and it was like, “make sure you sound like Scott,” you know what I mean? In his sometimes snarky tone. And the reality of it is, okay, I mean, it kind of worked. It was sort of funny, and it was two and a half minutes to build it and a couple of seconds to process and boom, like, there it was. It is amazing, but these are the things that I worry about as I think about it. Before we jump into the fun, Brian, just I need a piece of advice. You’re meeting, you’re at the bar. You’ve met some IT guy. You got literally 30 seconds. You’re clanking glasses, and he’s like, “You’re a smart guy. Tell me one thing, one piece of advice for this year and with everything going on that I should be focusing on.” What would you say?

[00:25:38] Brian Eichman: I would say align yourself with smart partners and, B, look at the comprehensive strategy, the kind of end-to-end solution that you’re looking at. Don’t silo. 100%. These things are all interconnected with one another.

[00:25:58] Scott Kinka: Nothing’s a silo anymore, my friend. Alright. No, listen, I appreciate it. This was super great. I hope you don’t mind. I’m going to use “inference zones” in my daily speak. I’ll credit you when I do, but I think it’s going to take off. I like the description. It makes a ton of sense as we go through that. Let me soft-land you into some fun here with staying slightly on topic. Give me a contrarian opinion about everything that’s going on in AI and infrastructure and hybrid work that you feel like you hold dear, but you feel like other people would not agree with you on. Be controversial for me.

[00:26:29] Brian Eichman: That it falls flat. That we’ve overbuilt, that we’re in a bubble, and this will go away.

[00:26:36] Scott Kinka: Interesting. And you believe that or you think that’s a possibility?

[00:26:41] Brian Eichman: I think it’s a possibility. I don’t believe it, but I do believe the hype train is in full effect right now. I think there will be some rationalization.

[00:26:52] Scott Kinka: Are we doing cloud all over again right now? Go get some.

[00:26:57] Brian Eichman: I like to think of waves. We did Internet. That was the first big wave that probably started you and I’s career. Cloud was the one that kind of projected us, and now we’re in the AI wave. And in each one of those, there was always the hype was early on, and it was big, and it rationalized a little bit.

[00:27:17] Scott Kinka: Totally. Makes sense. Some of these questions you know, but since it’s 20 months later, I want to update them. What are you reading right now? When we last talked, you mentioned coaching. You’re telling us how much of a student of the game of soccer you are. Is that still dominating your, uh, your reading, or is there something else that you’d like to recommend to the listeners?

[00:27:34] Brian Eichman: Kids’ athletics are always a big part of my life, but I just finished a book that was really cool. I think it ties well into our industry, telecommunications. It was a book called Artemis. It was by an author named Andy Weir. He wrote The Martian. It’s a really cool book, and I didn’t realize when I bought it, um, I was just traveling for work, and I went through, like, the Hudson news and got a bottle of water, a bag of beef jerky, and a book. And, uh, that it was about telecommunications, but we’ve colonized the moon. I won’t give the story away, but we’ve colonized the moon. There’s all sorts of drama going on up there. We’ve got the haves and the have-nots. There’s something really cool that’s being manufactured on the moon, and, uh, I’ll kind of leave it at that. But it was a really cool story.

[00:28:21] Scott Kinka: Well, you know what’s cool about that? Yes, it’s fiction, but I think in a lot of sci-fi, it’s also a little bit of soothsaying about technology. I was in a conversation at an event a week ago and somebody raised their hand, and they were like, “Well, you know, every time somebody asks AI about about how to keep the world green or how to ensure our survival, you know, they answer, ‘Kill the humans.’ Like, why is that? Why does AI want us dead?” Like, and I was, and my answer was, “These are large language models. They’ve been informed on the script of every sci-fi movie that we’ve been watching. So why are you surprised?” Right? It’s kind of this idea. Like, you’re thinking about that now. I mean, I wonder how much of the eventual colonization of the moon and the concepts and the concerns that people have will flow from media that’s coming out now.

[00:29:07] Brian Eichman: A lot of technology began in a fiction story somewhere, and, you know, 15 years later, here we are, right?

[00:29:16] Scott Kinka: Oh, I always use the example, like, Asimov wrote the three laws in I, Robot in the ’40s. You know what I mean? I think it was or early ’50s. And they’re reasonably pertinent today, by the way, given something that…

[00:29:30] Brian Eichman: I’m a movie guy. That movie’s kind of an acquired taste. That I think a lot of people aren’t a huge fan of I, Robot. I personally love it.

[00:29:37] Scott Kinka: Yeah, me too. Fantastic. Alright. Two more. I asked you for an end-of-the-world app last time. I said or maybe I didn’t. Does this question is this looking surprising? Like…

[00:29:46] Brian Eichman: It feels vaguely familiar here.

[00:29:48] Scott Kinka: The dystopian future hits us. You have one app working on your phone, and the fact that our producer didn’t share with me, maybe I didn’t ask you the question. What would your app choice be?

[00:29:58] Brian Eichman: Oh, this, I don’t know if this is, like, a good one or embarrassing or what, but I like to play spades. And I think card games are a lost art. Like, nobody plays card games anymore. I play spades on my phone because I can’t get anybody else to play with me live, you know, at the kitchen table, so I want spades.

[00:30:18] Scott Kinka: Alright. I love that. I mean, listen. In your end of the world, you’re alone in a cave. At least you’ll have something to do then, right? So good to go. Alright. Now, shameless prediction. I’ve got to have some fun with you, though, because the last time we talked, it was November ’23. Your prediction was, “The Chiefs will win their next game.” Was all you said. You said, “I’m not committing to another Super Bowl at this point.” As our fans know, and you probably know from then, I am also an Eagles fan. So I don’t know that this is as much a question as a small opportunity to gloat. It’s over now. What is your shameless prediction for the next 12 to 24 months? And do you care to double down on any kind of NFL type of prediction?

[00:30:57] Brian Eichman: I did go back. Told you I was in the way back.

[00:30:59] Scott Kinka: Okay. Go.

[00:30:59] Brian Eichman: So, just to be clear, we actually recorded this last time on 09/20/2023, and the Chiefs did win our next game. We did lose to the Eagles that year in the regular season, but we went on to win the Super Bowl. Okay. But you guys absolutely destroyed us last year. Congrats to you. All good. Now for my prediction this year, I think T. Swift and Travis Kelce, they become, you know, maybe husband and wife.

[00:31:36] Scott Kinka: Tie the knot. Alright. I like it.

[00:31:38] Brian Eichman: Tie the knot, man.

[00:31:39] Scott Kinka: I like it. Jason Kelce lives around the corner from me at the beach at the Jersey Shore. So we, uh, we don’t see T. Swizzle because she doesn’t come. It would be a craziness, but he hangs out on the beach and throws bags right around. So all good, man. We will check back on that prediction the next time you’re on here. Let’s not let it be 20 months, but this was a great, uh, great conversation together. I really enjoyed our time.

[00:32:01] Brian Eichman: Yeah. Well, I appreciate you, Scott. You do a good job with this. Bridgepoint’s a heck of a partner to CoreSite. We appreciate the platform.

[00:32:08] Scott Kinka: Well, fantastic. Brian, if listeners do want to share a little bit more, learn a little bit more, dig into that, I mean, I mentioned some blog entries, etcetera, how best to follow you?

[00:32:17] Brian Eichman: You got it, man. I’m not much into social media, but I’m on LinkedIn. CoreSite’s got a well-established web presence and social presence, YouTube, all of that stuff. I’m more of a pick up the phone and call me kind of guy. And, uh, you email, you call me anytime. Glad to work with your customers and any partners you have, so look forward to it.

[00:32:38] Scott Kinka: Well, Brian, thank you so much for your second appearance here. Only a couple folks who’ve been back for a second time, and that’s because we’re trying to spread it around. Our work has been so great with you guys. I find our conversation so interesting. I’m thrilled to have had the opportunity to chat with you again. Hopefully, we’ll do it again soon.

[00:32:54] Brian Eichman: We appreciate you, Scott. You have a good one.

[00:32:56] Scott Kinka: Awesome. Well, that’s a wrap, gang, for this episode of the Bridgecast. I thoroughly enjoyed it. I hope you did. If today’s conversation gave you something to think about, make sure you hit subscribe. If you’re watching us on YouTube, smash that follow button. Leave us a review. Share it with your team. Hopefully, there were some good nuggets here that you can take back and take some action on. And until the next episode, we’ll see you.

[00:33:18] Brian Eichman: Take it easy.

[00:33:19] Scott Kinka: Listen, if you made it this far, there must have been some good content, or you’re just a fan or a relative of mine. In either case, we appreciate you spending your most valuable asset with us, your time. We don’t take that lightly. We’d also like to say one more time that we’re appreciative of Bridgepointe Technologies and their belief and sponsorship of this show. We hope that if you or someone you know is thinking about your company’s digital transformation or simply the next IT project that you may not have the resources, budget, or time to get to, I’m sure that Bridgepointe, one of the country’s fastest-growing technology advisory and procurement firms, can help. Check out bridgepointetechnologies.com. Don’t forget the ‘e’ on Bridgepointe, or simply reach out to me at skinka, s-k-i-n-k-a, @bpt3.net. Also, take a minute, please, if you would, to give us a five-star review on your favorite platform. It helps give us the visibility to reach other people like you. Thanks, thanks for listening to this episode of The Bridgecast. I’m Scott Kinka. And until next time, there’s a lot of noise out there in business and in life. Do what you can to be the signal.