2965: How Digital Realty is Driving AI Growth Through High-Performance Infrastructure

[00:00:01] [SPEAKER_01]: Have you ever wondered what powers the Digital World were living? From streaming your favourite shows on Netflix, Disney Plus or Amazon Prime, to the latest advances in artificial intelligence?

[00:00:15] [SPEAKER_01]: Well, at you until a little secret, each data centers. And today I want to dive into this fascinating topic with Seamers Dunn, Managing Director of Digital Realty,

[00:00:27] [SPEAKER_01]: and Seamers will shed light on how AI is driving a massive demand for compute power. And how Digital Realty is responding with cutting-edge infrastructure solutions,

[00:00:38] [SPEAKER_01]: and we'll also explore the importance of local investment in data centers, particularly here in the UK, a discursely evolving needs of AI workloads.

[00:00:47] [SPEAKER_01]: So, whether it's training complex models or ensuring low latency access for AI applications,

[00:00:55] [SPEAKER_01]: Digital Realty is at the forefront of making it all possible.

[00:00:58] [SPEAKER_01]: Now obviously hosting a daily tech podcast comes with its challenges, and so I'm incredibly grateful to our sponsor for their essential support.

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[00:02:17] [SPEAKER_01]: So, book it up and hold on tight as our B-Mail is all the way to London where CMMC is going to join us today and uncover the critical role of data centers in this digital age,

[00:02:27] [SPEAKER_01]: and why standing still could mean that you're falling behind very fast.

[00:02:34] [SPEAKER_01]: So, a massive while welcome to the show, can you tell everyone this thing a little about who you are and what you do?

[00:02:40] [SPEAKER_00]: Any other thanks for having me. My name is Shane Miston. I run digital realties business in the UK and Ireland.

[00:02:48] [SPEAKER_00]: Digital reality is a call-ocation services provider and interconnection provider, so we build and manage data centers for IT infrastructure all over the world.

[00:02:58] [SPEAKER_00]: Six continents, 300 data centers, one of the only two publicly quoted data center service providers in the world and the largest by capacity.

[00:03:10] [SPEAKER_00]: Prior to that I managed a business in global business in Hula Park, an IT services business out of Texas, so I lived in Texas for a few years before coming back to Ireland and now I split my time between Dublin and London.

[00:03:24] [SPEAKER_01]: Fantastic. Webout in Texas is a two-end-up.

[00:03:26] [SPEAKER_00]: I lived in Houston in Texas. Very your electricity bills are more expensive than the Ireland winter.

[00:03:34] [SPEAKER_00]: Because the aircolumn, the recently is no winter. Wow. Very hot and humid, but a wonderful time there.

[00:03:43] [SPEAKER_01]: Fantastic. One of the reasons I invited you to join me on the podcast today is there's a lot of hype around AI at the moment. We've all seen it, but first of all I try and focus on the business problems that AI can actually solve.

[00:03:54] [SPEAKER_01]: Get beyond the buzzword. Another thing that we don't talk about, you know, if I just talk about energy prices days, AI is an energy problem and this demand that it's causing on our energy infrastructure right now.

[00:04:06] [SPEAKER_01]: So just to set the scene, how are you seeing the rise of January to AI?

[00:04:10] [SPEAKER_01]: Not always across businesses in every industry influencing the demand for compute power.

[00:04:15] [SPEAKER_01]: And I'd also want specific responses, a U.S. digital reality implemented to address this increase need because it is a big problem isn't it?

[00:04:25] [SPEAKER_00]: The growth of compute power and infrastructure from required requirements from artificial intelligence and generative archivist intelligence are real and very large and big.

[00:04:37] [SPEAKER_00]: The growth. So what one thing let me say is there was in a lot of growth in compute and IT infrastructure based on public cloud services.

[00:04:47] [SPEAKER_00]: And the thing about public cloud services is in the name cloud, it's like it's up there, it's kind of, it's a way infrastructure is not something you should worry about is the whole implication of this idea of a cloud.

[00:05:00] [SPEAKER_00]: So so public cloud services and what became hyper scalars then to provide them that kind of made people feel like infrastructure wasn't a thing something you hit away.

[00:05:12] [SPEAKER_00]: However, it was always a huge demand for growth and drove the requirements for IT infrastructure in data centers AI particularly with chatGPT, with Microsoft supporting them.

[00:05:24] [SPEAKER_00]: And with the growth of Nvidia have shown that actually IT infrastructure and the compute power associated with that is intrinsic to how you can run any IT platform.

[00:05:35] [SPEAKER_00]: There's a stack that goes from the hardware, the facility of the data center to power required for it to the software that runs on us.

[00:05:43] [SPEAKER_00]: So the growth of AI has really driven more and made it more front and center that IT infrastructure is critical to how you can grow any IT and utilize software.

[00:05:54] [SPEAKER_00]: So Nvidia's GPUs or any GPUs that are required to run artificial intelligence and train large language models require a high density of compute and a high density of power to drive that compute.

[00:06:10] [SPEAKER_00]: And that's real and what's very hungry for power around the world so the growth is kind of want to say exponential in terms of the power required on the data centers that are required to have as that infrastructure.

[00:06:22] [SPEAKER_00]: The digital reality is building AI ready data centers and by AI ready it really means that you can handle the density of power required to run those GPU platforms, which means instead of 5 to 10 kilowatts per rack of servers.

[00:06:39] [SPEAKER_00]: It's more like 100 land upwards that requires different cooling systems usually liquid the chip cooling so you got to get a liquid around the processor to cool it down, rather than cold air blowing to do data center.

[00:06:54] [SPEAKER_00]: So the densities and the design of a data center to run these AI language models is significantly different than what was required in the past 10 years.

[00:07:03] [SPEAKER_00]: So that's what we're building out all over the world where it's required which really means the United States to start with so that's where the main growth has been.

[00:07:12] [SPEAKER_00]: Europe is kind of catching up not catching up with regulations I'm at ads it seems to run ahead on that but certainly catching up with the deployment of AI infrastructure.

[00:07:22] [SPEAKER_01]: The power challenge aside of course, AI is only as good as the data that you feed it and the more data that you feed in often the better results that you get so I've got to ask it in what ways are you seeing AI fueling the demand for data storage to as well as management solutions and how are you ensuring efficient access to that data because again as well as challenges we don't hear too much about but again big one run.

[00:07:47] [SPEAKER_00]: Yeah it's really you say data storage is really compute power that's stored in the infrastructure requirements data data is the fuel right data is the goals I mean this is all about what you do with data and how you turn it into intelligent useful outputs and workflows.

[00:08:08] [SPEAKER_00]: So to train large language model you need to feed it data you don't necessarily need to have a network fabric that moves that data around for your transient training a language model.

[00:08:21] [SPEAKER_00]: So you'll generally be able to put that where you can avail a power at a reasonable cost and then deploy inference where you can take the intelligence from a large language model and utilize it for the business or the consumer more locally around where data gravity exists which is usually a large metro area.

[00:08:40] [SPEAKER_00]: So you need inference to really make use of the large language models where data gravity exists so in Europe that's basically long that Amsterdam power is Frankfurt places like that in North America be around for genius Atlanta Dallas LA.

[00:08:56] [SPEAKER_00]: Yeah, just that answer your question.

[00:08:58] [SPEAKER_01]: Yeah really does and before you came on the podcast today I was also doing a little research on you and I was reading how AI enabled applications actually perform better when deployed closer to the data centers and the support in infrastructure can you expand on that for anybody listening this not obviously seen or heard about this.

[00:09:18] [SPEAKER_00]: Yeah well so physics is a thing it is limitations so a network fabric to move data around requires minimizing latency you can get you can do a lot of the AI training remotely where you're building up the intelligence of the model.

[00:09:38] [SPEAKER_00]: But to utilize that and build it into workflows particularly for the business or consumer you need to be closer to where it uses is.

[00:09:46] [SPEAKER_00]: I'm sitting here in London and there's generally a trend to want to be in the west side of London or the Docklands or perhaps the center of the city.

[00:09:55] [SPEAKER_00]: And that's true in most major metropolis is where you want data infrastructure to apply the inference that you're getting from large language models to have the latency to be used where the branch office or consumers required them to be used.

[00:10:11] [SPEAKER_00]: So it's not so that network proximity and a lot of the reasons why it would be west along for example there's a predominance of data centers data center growth is decade or more building up a fiber links that that's how.

[00:10:26] [SPEAKER_00]: Data is moved is true fiber to light sources digitally infrastructure to light sources and you know that fiber infrastructure has been laid and developed and the capacity for it has been put in place.

[00:10:39] [SPEAKER_00]: And that's not easy to do so you want to build on where does best exists.

[00:10:43] [SPEAKER_01]: And I think you mentioned a few of them a few moments ago, but what the main data center hubs support and gay eye today for what you're seeing and how are you digital reality.

[00:10:52] [SPEAKER_01]: How are you investing in these areas to help countries like the UK and I'll know here to compete in this area.

[00:10:58] [SPEAKER_00]: Well, let's say there is no so we're at a fairly early stage with artificial intelligence and how it will grow so there's quite a few unknowns.

[00:11:09] [SPEAKER_00]: But we do know what's happened to the growth of cloud IT infrastructure.

[00:11:14] [SPEAKER_00]: And when we're those availability zones for cloud services I've build up and grown the trend will be to want to piggyback a little on where cloud infrastructure has for AI.

[00:11:27] [SPEAKER_00]: But actually it's a very different use case.

[00:11:30] [SPEAKER_00]: So first of all the huge compute to require compute power required to train language models for AI models that can sit remotely so there's the opportunity to build the facilities where you can train the models.

[00:11:46] [SPEAKER_00]: To be more remote standard major matrices so in the UK you might see data centers built in the north of England.

[00:11:56] [SPEAKER_00]: You might see them built at in the Nordics in North America they'll be built at where there's power available so that could be the Columbia River Gorge for example, I now swear is so where's the power available.

[00:12:09] [SPEAKER_00]: Where can you get the land, the power and train the models now where those models are used to be inference deployments which would also be very significant.

[00:12:18] [SPEAKER_00]: And we have to have proximity to where the workflows are for the business or where the consumers are and that will of course exist for all the current major data gravity zones are in Europe that's for sure London it's Frankfurt it's Paris it's Amsterdam in Asia it's Tokyo Singapore so when North America it'll be around North Virginia Atlanta Dallas Seattle LA Chicago.

[00:12:48] [SPEAKER_00]: New Jersey so those places will all require the growth of inference but the large language model training can be quite remote.

[00:12:56] [SPEAKER_01]: And you mentioned a lot of the usual suspects there North Virginia stands out why why is North Virginia such a hope in that area.

[00:13:03] [SPEAKER_00]: I bear in mind when I say North Virginia it's around the Washington DC area and it is probably our presence the largest cluster of data centers in the world.

[00:13:15] [SPEAKER_00]: And the reason being it's it's built up as a connectivity hope for North America and it's where cloud infrastructure is really built out in the largest portion in the North America region.

[00:13:29] [SPEAKER_01]: There's also a lot of talk at the moment about the current split between AI training and influencing workloads.

[00:13:36] [SPEAKER_01]: I'm curious how do you see that evolving over time like said we are in the very early stages at the moment but how do you see that evolving and what implications do you think that shift will have an infrastructure requirements for any IT direct is listening.

[00:13:49] [SPEAKER_00]: Yeah the training will require let's say orders of magnitude of a hundred megawatts of power in the cluster maybe upwards of that and you will really need to find where the power for that is.

[00:14:03] [SPEAKER_00]: And then what the latency requirements will allow it to be five remote so where is power available where is renewable energy available at a reasonable cost.

[00:14:13] [SPEAKER_00]: So that would be the driving factor there which will tend to be in Europe the the Nordics really but also where you can find people so people and.

[00:14:23] [SPEAKER_00]: But a human resources and skills required not just for the infrastructure but the AI modeling you can't be you're going to make a lot of priority decisions based on having building up your organization and having the resources and skills you need.

[00:14:39] [SPEAKER_00]: So that can be a little different for the training models but very infrastructure based which kind of it's so remote that you can't get the resources.

[00:14:49] [SPEAKER_00]: The inferencing is where you really make use of those models so inference deployments would still be significant five to ten megawatts or so it's not just a network node it'll be where IT infrastructure is driving use and the benefit of an AI model.

[00:15:06] [SPEAKER_00]: So that will need proximity to where the workflow is being run by the business but it's significant deployments.

[00:15:14] [SPEAKER_00]: It's not small like a network node of a couple hundred kilowatts this is a few megawatts of.

[00:15:20] [SPEAKER_00]: Of IT infrastructure power requirements and it will require you also to have proximity to the skill resources that are really managing that IT infrastructure and building software that drives the benefit from it.

[00:15:35] [SPEAKER_01]: And something else I also want to mention I mean to a lot of conferences on this side and the other side of the bomb this year and last year this simply a bit it's certain amount of apprehension whereas this year.

[00:15:46] [SPEAKER_01]: It seems to be all about adoption everyone's going all in on AI so how you did your tool reality preparing for the expected increase in influencing workloads as AI models become more mature become more widely adopted it must be an exciting time for you.

[00:16:02] [SPEAKER_00]: It is a very exciting time it's you really have to take this very seriously in terms of how real the adoption of AI is and it's still early days so.

[00:16:15] [SPEAKER_00]: What the way we are looking at it is we're the biggest data center infrastructure and services provider in in the world we have to keep ahead of this but we can't do everything.

[00:16:27] [SPEAKER_00]: So there's huge demand for power and infrastructure for training models so we'll do some of that as we are in in North America and here in Europe particularly I have to say in the UK.

[00:16:41] [SPEAKER_00]: And we'll then innovate around the design of those data centers so the design of these data centers has to be very different because of the density the cooling the management of them.

[00:16:54] [SPEAKER_00]: The one rack of servers roll into a data center now is requiring 10 to 20 times more power but also waste also how it's wrong how it's managed how it's maintained that all changes the density of cable requirements for the data in and out so we want to make sure that we're leading in terms of innovation around the solutions for that type of infrastructure.

[00:17:20] [SPEAKER_00]: We also partner so our view is well at our view it's for certain that a lot of the deployment of AI infrastructure for business would be done as a service the way cloud is run right now for the near term of people figure it out so with the B.

[00:17:39] [SPEAKER_00]: GPUs graphic processor units as a service in a cloud based model so that will be from one of the main high prescalers that are building their models so Google Amazon, Matha, Microsoft Oracle all building large models and then there's other people who are deploying infrastructure such as as cool we fear who made huge announcements in the UK.

[00:18:04] [SPEAKER_00]: Who are which are building a huge infrastructure and selling the GPU power as a service to high prescalers themselves or to actual businesses will then.

[00:18:14] [SPEAKER_00]: Run those models and see how they work, how a much benefit can they get from the workflow and that's what's happening to right now to financial services manufacturing retail to varying degrees depending on the business.

[00:18:27] [SPEAKER_00]: As that mature is going into next year and beyond but there'll be a realization that the main benefit comes from the value of the data I own so.

[00:18:36] [SPEAKER_00]: Being able to avail of AI models to a cloud model will be very beneficial which you'll also then want to build your private AI models using your own proprietary data to really build a lot of value and then we'll see not just hyper scale.

[00:18:52] [SPEAKER_00]: AI and training and inference models deployed we start to see private AI so where a company is deploying its own IT infrastructure to build its own AI models and get more inference from that for its business not just to the cloud.

[00:19:09] [SPEAKER_00]: So this whole so what it really means is IT infrastructure strategy has become key whereas for the last 20 years maybe 15 years since the deployment of Amazon web services launched in your EC2 service the elastic compute service which we began this model of cloud computing.

[00:19:29] [SPEAKER_00]: For the last 15 years it felt like the need for IT infrastructure was abstracted away I really just focused on my application and software development.

[00:19:39] [SPEAKER_00]: AI has really brought back the fact that you need an IT infrastructure strategy where you deploy the facility itself the racks the servers the networking switches and the software it all has to be built together.

[00:19:53] [SPEAKER_00]: And that's kind of a realization that it never went away but with people with this concept of cloud sort of lost track of so we're going to build that infrastructure for some some work for large language models in more remote regions but certainly for high density AI inference deployments in large metros or data gravity exists.

[00:20:14] [SPEAKER_01]: And as you said we have to get ahead of this thing and you can't do it all on your own so can you tell me how important local investment is in data center infrastructure especially for supporting AI advancements and driving that economic growth.

[00:20:31] [SPEAKER_00]: Do you see this happening at how important isn't artificial intelligence has been deployed for many years it's just gone to a whole new level with the launch and realization of a jack chat GPT could do.

[00:20:45] [SPEAKER_00]: And generator AI now is fully understood as I had a whole other set of intrinsic value to workflows and applications that you can have to run your business.

[00:20:56] [SPEAKER_00]: As well as consumer applications that were all kind of aware of how you can have a better essay for your English a levels but that's fun sort of consumer stuff but businesses to run their businesses have to adopt AI we're going to have.

[00:21:27] [SPEAKER_00]: And so if you don't it's a bit like digitization if you don't adopt that digitization for your business you're probably going out of business every business is digital and really every business is going to have to adopt AI at some level or other.

[00:21:42] [SPEAKER_00]: So for that you need infrastructure so if you're going to deprive your jurisdiction of the infrastructure required which be the means physical data centers with the infrastructure in those data centers with a network and a fabric connecting all of that.

[00:21:58] [SPEAKER_00]: If you're not going to get ahead of that in your jurisdiction you're going to fall behind like standing still is falling behind very fast I think the UK is doing an excellent job I have to say I think the manifestos I'm reading all talk about growth I think.

[00:22:17] [SPEAKER_00]: The legal infrastructure the regulatory infrastructure the regulatory approach here is is excellent and we're seeing the deployment happen here preferentially what's happening.

[00:22:29] [SPEAKER_00]: With AI infrastructure deployment is the United States is racing ahead I mean it is far ahead and in this as is not on typical for.

[00:22:40] [SPEAKER_00]: I.T infrastructure in general this where cloud began web the what the the internet API Europe has to catch up a lot quicker and is there's a lot of green shoots around it the infrastructure deployment in Europe pretty slow and I think there's a bit of a mismatch between over governance and regulation versus deployment of AI the bit too much fear.

[00:23:05] [SPEAKER_00]: I'm wondering about it but you know we've had a really excellent deployment in Copenhagen with the day the Danish government and no one orders with us in a day the center deploy huge cluster of.

[00:23:17] [SPEAKER_00]: I think the advanced in video chips for AI deployment and research there's been a number of announcements in the UK and I think it here a lot more coming soon.

[00:23:29] [SPEAKER_00]: But there's other countries that are are not adopting very fast so I'm in a passive way I can tell you in Dublin it's falling hugely behind because of a moratorium on data centers fear of data centers even before AI arrived.

[00:23:43] [SPEAKER_00]: So no no identity of a structure has been deployed in Dublin so Dublin's falling behind and investments are being made preferentially in places like the UK democrats I said.

[00:23:53] [SPEAKER_00]: Spain there's a lot of deployments there's a lot of power it's reasonably cheap and certainly in the Nordic snow away and Sweden so it it's critical if you don't if you don't deploy.

[00:24:04] [SPEAKER_00]: And move ahead to take advantage of these this technology your economy's going to fall behind so there needs to be some sort of rational connection between regulation sustainability and environmental concerns and economic growth all of which can go hand in hand some people like to think that they're mutually exclusive goals or not sustainability with economic growth and is more than feasible impossible.

[00:24:33] [SPEAKER_01]: And for any non-techy business leaders listening to our conversation day today just to bring to life everything that we're talking about and the importance of everything we're talking about.

[00:24:43] [SPEAKER_01]: Can you just say I expand on how data centers actually enable everyday online activities from streaming video calls ecommerce and a what role do they play in supporting the latest innovations in AI because it increasing it feels like they've become the lifeblood of businesses around.

[00:25:00] [SPEAKER_00]: Yeah, well I mean we're talking on a zoom call right now and that's going to a data center if if there wasn't IT infrastructure and hardware deployed in a data center.

[00:25:30] [SPEAKER_00]: around for the health and well being of the nation it's certainly not of the same.

[00:25:36] [SPEAKER_00]: criticality but our engineers were also considered critical resources because you couldn't run the economy if our data centers didn't operate.

[00:25:46] [SPEAKER_00]: you couldn't have capture card for remote for payment you couldn't have an emergency call center for ambulances you couldn't have the data from medical care arrived the research for.

[00:26:00] [SPEAKER_00]: the drugs that got us out of the pandemic couldn't have occurred and we couldn't have worked remoking so I mean there are just some examples but every business runs applications to make its business work the days of paper ledgers and just.

[00:26:17] [SPEAKER_00]: the word of mad communication that it's a digital world and if it's digital if it requires a data center that's what I mean by this idea of clouds seem to abstract the infrastructure way when I'm using my iPhone and I'm storing the photos it's in the cloud.

[00:26:32] [SPEAKER_00]: it makes it feel like it's in a fluffy white place but actually that's a data center.

[00:26:38] [SPEAKER_00]: Apple's data center is the cloud that's a story you photos from your iPhone or that's a running the application that already game you're playing or.

[00:26:48] [SPEAKER_00]: the business financial model that you're running it all goes to have to an IT infrastructure stack and that includes the hardware and the physical hardware has to reside in a data center which by the way is the most efficient place you can put it a lot of businesses run.

[00:27:06] [SPEAKER_00]: IT on a floor in your office building the call it a computer room or so so we the number of firms for example in the documents here who are exiting their offices when consolidating since the pandemic.

[00:27:21] [SPEAKER_00]: the biggest inhibitor to the moving is our IT infrastructure in the basement or the tenth floor or something.

[00:27:29] [SPEAKER_00]: at its a terribly inefficient and environmentally bad way to run your IT infrastructure.

[00:27:34] [SPEAKER_00]: run them in a highly efficient modern data center where you can transfer data center in communities of relevance to you with networks and with far more efficiency and sustainable energy being used.

[00:27:50] [SPEAKER_01]: Well I cut up thank you for coming on here and sharing your incredible insights today and shanning a light on this critically important topic but before I let you go I'm going to ask you to leave one final gift for everyone listening you mentioned today how you do a lot of flying.

[00:28:04] [SPEAKER_01]: around the world I suspect that involves more than a few books along the way so is that a book that you could recommend that we could add to our Amazon wish list and it could be anything at all but what would you recommend and why.

[00:28:17] [SPEAKER_00]: Yeah, thanks for asking our question Neil I do get to read a lot and I love reading educating yourself as one of the best things you can do.

[00:28:25] [SPEAKER_00]: I thought of business books that I could mention but actually the one that I really enjoyed reading and so much so I re-read it is sapiens it's a book that really tries by it is really professor who's in a story and he tries to explain why humans why homosafience had we become.

[00:28:44] [SPEAKER_00]: But why did we become the dominant species at her iris in his name he is basic premise of the book is we leap forward a lot of things happen to possible terms language cognitively forward book what he really said is.

[00:28:58] [SPEAKER_00]: What change humans made a difference is our ability to organize in large numbers and that was based on story telling.

[00:29:05] [SPEAKER_00]: The ability to tell stories which I told was a profound insight it's a far it's a long book so it's a far more it's not quite as simple as that but the ability to tell stories and.

[00:29:16] [SPEAKER_00]: Become communities because of the stories and myths we build up and I find that profound just from a.

[00:29:27] [SPEAKER_00]: I mean an an adjoining book that bring up is side Simon's in excess start with why so if you can explain things and tell a story around us.

[00:29:38] [SPEAKER_00]: You can lead people and organization so tell the story about a I would be a good human hope a save homosafience skill so sapiens.

[00:29:48] [SPEAKER_01]: Little for that while I want to both books two great books up both of those to our armors and we're sliced in.

[00:29:53] [SPEAKER_01]: But anyone listening just want to find out more information about you your work at digital reality and maybe start conversation we ask a few questions where's the best start in point for everything.

[00:30:03] [SPEAKER_00]: We're pretty the best place to find me is LinkedIn I think LinkedIn's a great professional network.

[00:30:10] [SPEAKER_00]: So you can easily find me shameless done digital reality and easily connected me on LinkedIn that would be a great place to start.

[00:30:17] [SPEAKER_01]: Well, I'll add a link to that as well as a link to the digital reality website and.

[00:30:22] [SPEAKER_01]: I'll show you how much I love to say we're coming to a lot of ground from how AI is fueling demand for data storage and management solutions and efficient access today.

[00:30:31] [SPEAKER_01]: And I enabled applications how they perform better when deployed close to data center and support infrastructure and also a timely reminder whether it is streaming Netflix zoom calls or online shopping.

[00:30:42] [SPEAKER_01]: We're even researching your next holiday everything we do online is enabled by data centers and as you said that if it's digital.

[00:30:50] [SPEAKER_01]: It needs a data center and standing still is actually falling behind very fast so many great takeaways but more than I think just thank you for showing that with me today.

[00:30:59] [SPEAKER_01]: Thanks Neil it was pleasure.

[00:31:02] [SPEAKER_01]: So as we've heard from seamless today the world of data centers is not just about housing servers it's about enabling the future of AI and indeed digital transformation and I think his insight shared today.

[00:31:14] [SPEAKER_01]: I like the importance of a robust IT infrastructure and why strategic investment to stay competitive is so important in this rapidly evolving tech landscape.

[00:31:26] [SPEAKER_01]: But as always let me know what you think about the future of AI and indeed data centers by email and the tech blog right at outlook.com.

[00:31:34] [SPEAKER_01]: LinkedIn just at Neil C Hughes at look here thoughts on this and please join me again tomorrow for another exciting conversation on a different topic here on.

[00:31:44] [SPEAKER_01]: Tech Talks Daily but more than anything thank you for spending a little bit of time with me today and until next time.

[00:31:51] [SPEAKER_01]: Don't be a stranger.