The API Economy Boom & Data Center Evolution | TSG Ep. 943

Hi, ho. Hi Ho. It's off to work.

AI Agents. Go. You are watching Textron Gang.

Hey everyone. Happy Monday. Monday.

Wow. Happy Monday. Lemme say that again.

Hey, everyone. Happy Monday. Where did the weekend go?

I'm Alan Shimmel. You're watching Text Drug Gang. We've got a lot to go over with you today.

As usual, it's a, a big fat dose of AI and some data centers thrown in, but we'll be talking about, excuse me, API security and whatever else pops up into our gang member, our panel of gang members, uh, mines today. Let me introduce you to our gang members. I'm really happy to have the two jacks.

It sounds like a movie with, but it's not Jack Nicholson. It's, it's Jack Poller. Jack P Yep.

If you could good morning. Could say hello. So we know.

Hello. Jack P And then we have Jack g Jack Gold, Jack, you there? I'm Here.

All right. So, we'll, we'll, we'll try to remember the G'S and the P's, but if you both answer to a question, we understand, um, joining the, the pair of Jacks. We've got a full house.

See what I did there? Um, Robert Reeves is with us and from, uh, Colorado fighting, fighting the bandwidth wars. Mm-hmm.

Our good friend Kimberly Bates. Hey, Kimberly. How are you?

I'm doing good. If the, the bandwidth would help, would cooperate. Well, luckily, our, our state-of-the-art recording system records you locally.

It was a lot of money sending a camera crew out there, but we're recording you locally and it, and it should all work fine. Um, guys, let's jump into today's this wonderful Monday morning topic. Our first topic is around the API economy.

Finally gets real just in time to turn out the lights on the way out. Uh, well, that's my opinion. Robert, you may have a different opinion.

What are we talking about here? Oh, uh, well, we're talking about, um, you know, how we integrate and interact with systems. Uh, do we as humans go to, you know, we go to a web browser, we're using a terminal command line, something where we're stitching together code to get systems to talk to each other.

And as we know from our friends in, uh, cloud native, uh, computing foundation, CNCF, that APIs are the way to go, that's the better way, superior way for systems to communicate. And what we're talking about here in an API economy is people delivering their systems via an API and, you know, alongside, um, you know, our, our GitHub actions or, or the, the web interface or scripting or something like that, a a Python module. Uh, so when we start building systems that are API first, they communicate with each other a lot easier.

And of course, this gives rise to the ability for a, a AI agents to do a lot of that work for us. Um, and so that's what we're starting to see. We're starting to see as more and more large enterprises and and individuals, uh, use agents, um, we're starting to see more consumption from companies that deliver their services via API for those agents.

And that's a good thing for certainly ai. And it's a good thing for those companies that are deliver delivering services by the API. We're also seeing something interesting, if I may jump in here, um, some companies that were closed off before, uh, are now opening up the API to generate revenue.

And, and a good example of this is the telco industry. You know, T-Mobile, at and t, Verizon, they all had their own networks. They all had their internal cores.

And what they've done now is come together with, uh, Ericsson driving this, uh, formed a, a new organization called duna that, uh, is actually providing API connectivity to the carriers. And the carriers are actually able to generate revenue on that. So, for instance, uh, you're logging into your financial organization and they wanna make sure it's really you, there's an API that they can address with the carrier network, um, on your, for your mobile phone to make sure it's really you that, you know, you're in your location, it's your phone, you have the right identity, et cetera.

And, and they're actually able to charge, you know, per perhaps pennies. But there are billions of these transactions going on. So there's real money to be had.

So the API economy is actually turning into a revenue based economy for a lot of companies that were closed before, but now find a way to, to generate real, real cash. Absolutely. Guys, I gotta tell you something.

2015 or so, maybe it was 2016. I'm in Las Vegas at a conference called ca World, Kimberly. I'm sure you probably right, Robert.

We've, we've all been there. Dude, I think I was there with you. You might've been, actually, you might've been.

I, now that I'm thinking about it, Robert, I'm almost positive you were probably one of your big Lebowski sweaters, remember? No doubt. And, and you were there.

Um, but they announced something called the API Economy that in the future applications, were gonna talk to each other via API and API, gateways and APIs were the way of the, it was going to go, it was gonna drive the whole economy. Now, two, three years ago, I remember talking to the folks at Akamai about their, uh, network report, right? Akamai carries a good percentage of the entire network, of the entire internet flows through Akamai, uh, CDN and so forth, a major, and, and CloudFlare as well.

A majority of the traffic on the internet today is actually APIs, talking to APIs. It's a lot of web to web stuff, but it APIs. So I would posit that the API economy has been alive and well, a long, a long time, but now we're starting to see people quantify the revenue associated with it.

However, there was a time when I first heard about Agentic AI that I thought it was just a fancy term for API, right? But, but APIs generally, and don't do autonomous tasks where agents can't. So my my question to the gang is, is AG agentic AI spurring this realization of how real the API economy is?

Does it eventually replace your APIs? Because APIs are rather dumb. They're just, it's like having a plug in the wall and you gotta an electric cord that you plug into it.

That that's, that's basically what it is, right? And the current's the same. So is a agentic AI spurring on the use of APIs?

Or is agen ai, you know, with a to a and and MCP eventually gonna replace APIs? I think that's the question. I don't think it's an either or.

I think it's a both. There's a lot of things for which we really don't need a, an AI agent or AI in general. There's a Here Heresy Yes.

Last for me. But it, but I mean, there's a, the, I think the api, the API economy has been around for a while. It's just hidden and not talked about.

For instance, um, there's, uh, a lot of, uh, email that gets Dr, uh, delivered by API that is done in the background, either bulk email or, uh, text messages. So, for instance, all of your two-factor authentication, when you log into some website and it says, I'm gonna, you know, what's your, it has your cell phone number, and it's gonna text you a code that gets driven through an API through either somebody who can hit the telco and generate, uh, uh, a text message. And that's all.

Again, as, as Jack said, those are all micro transactions in terms of dollar value. There is fractions of a cent per, but it adds up because it's bulk volume. And there's a lot of companies, this entire business model is based on that.

Uh, SendGrid for API for, uh, email is one, right? And you don't need an AI agent to be able to send an SMS text for two-factor authentication. You really don't, I would think, given the technology that the API is more efficient from an energy and server consumption than angen.

So there's a trade off there when you say how you're gonna do this. I mean, in terms of, you know, I know later on we'll talk about this, but the amount of energy that has to be consumed to produce that same result, why would I change if it's extra effort? Yeah.

Interesting. Uh, and Kimberly, I, I agree with you and Alan, to your point earlier. Um, all, all of these APIs traveling around using a bandwidth, imagine what's gonna happen when you have AI agents sending AI agents other information.

We're not talking about bits and bytes here anymore. We're talking about gigabytes, and it gets really messy very, very quickly. So, um, one of the reasons they came up with MCP and HA and all of that is they're, they're trying to, they get a, a, their hands wrapped around that right now.

And it's, it's not really working all that well. First of all, it's, they're very new protocols, so we don't, don't even know how well they're gonna work. But it could get really messy with agentic AI from a, from a data transmission perspective.

Well, you know, we, I think it was what, long time ago when, you know, I can remember Microsoft coming out with another operating system that would take advantage of, you know, more than a couple megabytes. And we said, how in the world are we gonna use it all? Oh, I'll use it.

Look, it, you know, it's the nature of, of, of computing for as long as I've been involved. I, I remember one time I bought, uh, it was a hard box. It was like, uh, it was about, it was about that big, right?

It was a, a external hard drive box that you can plug into your X 86 machine. And I, I wanna say it had 40 megs or 30 megs. Yeah.

And I said, my god, my God, how am I ever gonna feel this is gonna last me forever? Like, I couldn't believe. How much did it do you still use it?

Pretty much. Yeah. Yeah.

I gotta plugged in over here, you know, along with the drives. Remember, you know, big scuzzy, what's that noise? That grinding noise?

Oh, it's my hard drive. You know, they used to make noise. What's a hard Drive, Alex?

Yeah. What's a hard drive? Who's making daiquiris?

Why, Why, why do I, you know, it's funny, I, I was actually going through a, one of the junk drawers on our third floor. So we have a third floor office in my, in my house, in our townhouse, and we use it just as an office, a spare bedroom. And I have all my techie junk drawers in there with, you know, uh, serial port cables and like, all this stuff we used to use.

And I came across an external DVD, uh, drive. And I, first, I was like, what is that? And then I picked up, I said, oh, yeah.

I said, I wonder if it works, but I, I don't have a DVD to, to, to test it with. So anyway, you know, maybe a, well, I don't think APIs will go that way, but Well, that's, that's, you know, it's not, you know, we, we've been saying, you know, on the, the techie side of the house, we've been saying for years, oh, hey, we need to design API first, API first architecture even internally. And it, it, it's, it's like pulling teeth, you know, getting, uh, uh, business leaders to understand that.

Like, okay, let's take this old busted system, J two e, e three tier app, and, and come on, let, let's, let's at least do an API wrapper on it. Um, and the business side of the house was saying, no, no, no, we can't afford that. It's fine the way it's, well, I'm happy to see the revenue is driving the change, even though the geeks and the nerds were saying API first, API first.

And yes, we've gotten there and there's certainly examples of companies doing that. Winning. I love Twilio's API, and they, I believe they were one of the first to say, we're API first.

That's how you interact with us. Um, but it takes something like, you know, uh, this revenue increase for companies to say, ah, maybe it is the right thing to do. And, and, and Jack g you were talking about that with, uh, telcos.

Um, it's not because the telcos said, well, this is a better design, uh, pattern. They said, nah, this is where the money is. Right.

Right. You know, I think that highlights just the value of when you want to make change in an organization, you have to get both sides aligned. You have to get your techies aligned with, with the concept of, uh, of, you know, that, that, you know, technology, uh, uh, next step in, in, in technology advancement with next step in advancing the revenue for the company.

You've gotta align both of those. If you wanna make a change, even though as CTO me calling for API first, I need to also have the business side of it to convince, uh, my leaders, my, my, my peers, that it's a good thing and worth the investment. One of the challenges with APIs though, is that there's so many of them, there's no standards for APIs.

And, and what you really end up talking about or end up with is gazillions of APIs that often people can't use because they're, they're not, they're not really well-defined. Uh, and so I, I've seen companies that have built APIs that sort of build a spec around it. And then when people try to go to use, it doesn't just doesn't work.

They can't get to it. So it's not, it's not simply about creating an API, it's about creating one that, that people could actually use. Absolutely.

Well, this, back, back to what Robert was saying, is that whenever you're creating anything from a business aspect, you've gotta tie it to a return on investment. What's the value in doing this o other than saying I'm, you know, created an API. So it's like any other feature or functionality that we have in a technology is, it has to have a purpose.

Yep. Let me, let me give you my litmus test for how real or not it is. I, I think maybe four years ago, four or five years ago, one of the hottest sectors in the cyber space was API security Jack, Jack p you probably remember, right?

Mm-hmm. You had no name security. You had, you had one that Red Hat bought that, I don't remember.

You had traceable AI Traceable. There's a, there's a lot. There were a lot of players space.

There Were a lot. And it still issue, there was a big issue because people didn't even realize how many APIs they had that were talking to each other. It was such a majority of the traffic.

And everyone was talking API security, API security, API security. And as often happens in these, you know, new product, uh, the product becomes a feature of someone else's platform. And, and, uh, the first three companies who get out make a good amount of money, and everyone else is chasing scraps.

Um, you don't hear API security much anymore, do you? I don't hear Jack p do you? No, I think it's been, uh, subsumed into, uh, application security as a, a broader topic.

It is a, it is a feature set of how do you protect your application in general. And I think the, the challenge, going back to sort of the revenue side of it, the real challenge for people is not so much, hasn't been securing the API, it's been much more how do we account for it and do the accounting and the, the make sure we can collect the appropriate revenue for the API like, like Kimberly was saying, ROI It is ROS the API. All right.

Hey, right. We gotta, we gotta move on. Let's take a break.

And we are gonna come back to high hoe, a little snow white in the dwarfs, high hoe, high hoe. It's off to work. We go for AI agents.

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Hi everyone. We're back here on the gang. And, uh, as I mentioned before the break, we got a story or a topic we want to cover now about, you know, everyone's expanding their AI agent workforce and rolling out more AI agent functionality.

Um, or a lot of people are saying, great, show me where it's actually working. But Jack Gold, what do you think about this one? Yeah, there's a lot of experimentation going on with AI and, and agentic AI in particular, because people think that it's going to solve a whole bunch of problems for them.

The real challenge with it, well, there's multiple challenges. The, the first challenge is, how do I define the problem I'm trying to solve? And companies aren't necessarily good at that.

Second challenge is, if I'm using Ag agentic AI versus a human, is the process really the same? Can I just clone the process from people to technology? And often the case is that that's not the case.

You, you can't just do that. The third problem is that it's really hard to build agents. There's a lot of stuff that goes on from modeling to understanding the security orchestration.

You need to be able to access, and this is probably one of the hardest part, you need to really be able to access all the data within your organization that will feed that agent so that agent knows what they're doing and, and can do it accurately. And so what's ended up happening is that the early stage, uh, agents were built by companies putting together a, a toolkit. Again, you know, one from column A, one from column B, one from column C, put it together and try to get an agent that actually works and is producible and can be put into production.

Effectively, what we're seeing is that the big, uh, hyperscalers, the cloud providers are trying to do that, uh, are trying to make that a much easier process. And so this week as an example, Google, uh, uh, introduced its Gemini Enterprise product set. And what it really does is it, it puts a wrapper around, first of all, it's Gemini model, but also includes, uh, a series of access points for people who want to build agents, which in includes the orchestration capability, the ability to add information, uh, or search for and add information.

We just talked about APIs, the ability to find the APIs within your organization so they can bring in the app appropriate data so that these agents are working. The third piece of it is that it's also got to be able to run effectively with your other apps. So in Google's case, they're trying to tie it closely to their Google Workspace application, which is, is the, you know, their, their office equivalents.

And so what we're seeing is that companies are now looking at this from the perspective of, can I find a whole bucket w worth of tools in one place, well integrated so that I can make these agents work. And by the way, the bigger problem for a lot of companies is that they've used, uh, or, or they built these agents through it, through DevOps. The problem with that approach is that DevOps is resource restricted in most organizations and line of business users really want to take some of these agents and at least modify them, if not create them completely, uh, on their own.

They also wanna be able to exchange them. So a again, one of the things that Google is, is offering within their, uh, uh, enterprise platform. And, and by the way, AWS does this as well.

Microsoft's moving the same way, is a marketplace. I can throw agents into this marketplace. I can pull them out, I can modify them if I want to.

Um, maybe in the future it'll be revenue generating. I mean, initially Google is gonna build a bunch of agents that they'll put in, into this repository that you can then, um, pull out some for healthcare, some from retail, some from other, uh, scientific approaches. And, uh, eventually it's going to be a, a marketplace just like, uh, you know, Salesforce has their marketplace built around their products that Microsoft has.

So everyone has a marketplace these days. Um, so the, the intent is to say, eventually, okay, you need an agent. Somebody's already built it.

Don't, don't build your own, or at least don't start from scratch. Here's one that you can pull out the marketplace and go modify within our toolkit. And so it's really an all encompassing, by the way, it's also about lock-in.

These guys want you to get locked into their approach. Of course, uh, they already do that in the cloud anyway, and this is a cloud-based product. One of the things, by the way, it doesn't do yet, uh, and none of them do yet, is really be able to distribute the agent load.

So as we move to more localized AI capability for, for instance, a IPCs, there's stuff that you wanna be able to run locally. You don't want to have to send everything into the cloud, and that's a whole different other problem, but they're working on it. But that's something that we're, we're gonna see in a future product place.

Uh, how soon, who knows? But it, it, it'll come. So it, it's a, it's a very interesting space, uh, for companies to experiment with.

Right now, there aren't, there are some production systems. Um, the airlines have been using some of them. Um, some of the, uh, scientific community has been using them, but it's not widespread until, until we get to a point where people can actually track these things and say, yeah, I'm really getting an ROI by using this agent, as opposed to just, you know, going out and hiring a bunch of people, we're probably not gonna get real widespread adoption.

What I find interest interesting is, you know, you look at SAP and, and the case that we've highlighted here. You look at Google, you look at Salesforce, Dreamforce, you look at AWS you look at Microsoft, every single one of them says, we are agent agnostic. As a matter of fact, we could manage and, and give you access to everybody's agents.

You could use the agent of your choice, but we want you to use our agents, right? Or, you know, we, we'd like you to use our agents, you should use our agents because they give you this, this, and this. And so, you know, my, and look, kudos to Microsoft, I don't use it, but co-pilot, they built co-pilot into everything from GitHub, you know, to office, to, to Azure, everything.

It, it's one co-pilot. I think Google's following a similar track now. Well, That, that's More branding on, On, On co well, but functionality, right?

They, in another words, they're building a, an agent, their agent, you know, 'cause the, the underpinnings of their agents all have common code, right? Mm-hmm. Across, across their offerings.

SAP's doing it. Salesforce. Salesforce might have been the first one with Dream with, uh, yeah.

Agent Force. Um, the bigger problem though, Alan, is not, is not the agent. The bigger problem is the underlying model.

I Actually, I think there's a higher level story here. That's an industry wide story and a trend story that I think we missed. 0, right?

We are really in the same type of revolution, just much, much faster with ai. 0 was all about the, uh, large language model. And I think it's generative, but I think it was pretty clear that, uh, anthropic and Open AI sort of won that battle, right?

And it's a natural language interface, chat based interface. 0 is about the agents now machine to machine, or human to machine in a different way. And I think there's two separate battles going on here.

One is, what's the development platform? Who defines the development platform for AI agents? And Google is putting a stake in the ground on this part of it.

And I think that's what their announcement was, is about how do you build these things? Of course, using Google's tools. The second part of the battle is what infrastructure does that AI agent run on?

Is running in the Google Cloud, in the Microsoft cloud, or in the Amazon cloud. And that's an open battle right now. And Google wants that business, as does Microsoft and everybody else, right?

'cause they got a gazillion servers that they gotta keep occupied for this stuff, right? 0, Google came out with a very interesting pricing model, which is a per user month per seat user month model for the development platform. Now, Microsoft made an announcement, uh, last week or the last two weeks about their ai, uh, security solution.

And within that they have AI security development capabilities and for, sorry, AI agent for security development capabilities. And when you run those agents, development is free. But when you run them, it's based on processor hours similar to way we consume compute.

So it's a completely different pricing model going for a completely different customer and use case, but it's both agen ai. So Jack, you're talking about Just, just a, I'm sorry, just a quick clarification. Sorry, Kimberly.

I, uh, what's interesting about Google is if you read under the cover, read under the covers, yes, it's a per person per month charge. Unless you start using a whole bunch of CPUs in the cloud, pick up the cards. I missed that part, but yes, they, yes, because they, they, that money, They actually all have that though, that that unlimited is not truly unlimited.

Kimberly, Your point. Sorry, Kimberly. So you guys are talking about the platform delivery coming from a Google or from a Microsoft, but there's a much bigger piece in the AG agentic piece going on, which is highlighted by the piece that we talked about, SAP, you know, and kind of my belief that a lot of this agent, these agents will be delivered through the different ERP systems application systems.

You know, whether it's ServiceNow, SAP, Jack, Henry, you know, for the financial community or something like that. I mean, there's a zillion of these applications that are out there that if you look at what SAP rolled out, it's how do you use their systems better and improve their systems? So it's not just a, there's a platform play true, but that's also, are you, we also have to remember that so much of the enterprise's applications are still OnPrem, they're not in the cloud.

Yep. And so, yeah, that's great and fine and dandy, but where, where's the rest of these applications gonna go? And I think that it's, it's, it's, it is good that development's gotta happen through not just DevOps, but it's gotta happen through the ERP system.

And one other comment here as you Jack Gold, as you were talking about the DevOps, the ROI piece of it, what this appears to me is this is a product management issue. True product management to define what the business problem is. What are we trying to solve?

How are we gonna deliver it? Then defining what that is and handing it over to development to start putting it together. Once you've validated with the cu once you validate with customer, um, it's not just tell DevOps or, you know, the CEO saying, get me an agent, I need to be able to talk about it at my next release.

No, it is part of an additional feature or functionality coming out of the use cases that we're delivering on. So a, a slight modifications. I can't believe, though, I, I think if you read under the covers, what, what Google's trying to do, what Microsoft's trying to do, what a AWS perhaps not as aggressively trying to do, is they're trying to democratize this.

They're trying to say, Hey, if, you know, if you can do an Excel spreadsheet, which is a, you know, a line of business function, you don't send that to DevOps, then you should be able to build an agent. That's what they're trying to get to. Now, are we there yet?

Probably not. But that's the ultimate goal, making it a line of business function. You know, you and I build our own agents, or at least modify agents, um, without having to go to it because e eventually there are gonna be millions of these agents running around and, uh, it can't handle it.

I, I think this is also a fight for the soul of your IT department, right? Who, who is your go-to, right? Uh, you want to talk about pass winners, losers, o obviously Microsoft over the last, for, you know, 30 years, 40 years, has, has owned the hearts and minds of most desktop users, of most personal computer users of mo.

They've had the greatest developer channel. They, you know, look, hate 'em or love them. They are who they are, right?

Um, AWS you know, when we talk cloud, a lot of people, it begins in ends at AWS, apple has their fanboys and everything else. This is the next battleground for who's your go-to, right? They, for a lot of companies, their ERP solution, their SAP is, is the heart and soul of their IT for other companies, it's their Salesforce, right?

And all of these companies are vying to be your agent manager. So it's not just their agents, but your agent manager. 0, as Jack would call it, right?

This next phase of, of, of, uh, the a AI maturity curve. Well, A and one of the things that Google was of course, pounding their chest about in their announcements about this is, you know, it's all built on Gemini. And I think we're going to very quickly realize that the underlying model is not that important to agentic ai.

It's really all of the other stuff that it integrates with and how it works in concert with everything else. That becomes the key and not the model itself. And, and being able to grab your own data to personalize whatever model is the underlying model that's really ultimately gonna be the key.

If you're, if you're Delta Airlines, you don't care what's going on at at United or American, you wanna be able to pull your own data into that model. Well, that's what was interesting about the Google announcement, is they explicitly said, we want you to be able to access your data, because we understand that's the basis for agent ai. And they called out explicitly Microsoft 365 as being able to get your data.

So they've already conceded essentially that your data lives in Microsoft, not in Google's office applications, right? And they said SharePoint as well. SharePoint, Right?

So they know where the data lives, And they also stress that they're not abandoning, you know, Google search. That becomes a key component of this capability, because ultimately you're gonna use that search capability within your own organization to find the data that you need to make your model work or to make your agent, they, they've Been dangling. Google is the, the key to making your own organization better for a long time.

Sure. Hey, Rolling Stones always play satisfaction. Yeah, okay.

You know, you always, always gotta give them what they came for. Absolutely. All right.

Hey, let's take a break, A break here. We'll come back for our C block. We're gonna talk, we're gonna talk data centers, next gen data centers, aren't they all?

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All right, here we go. C block in three, two. Hey everyone.

We're back here on the gang. You know, last Thursday I did, one of my shimmy says short videos on LinkedIn and X, and it's, it's probably available on YouTube now too. Um, but really, it, it was the tale of two, two cities here.

One is the city of AI and one is the rest of the economy. And, and we, we, we live, we live in, and that's where we're living in, right? Over half of the GDP growth in the US is directly attributable, attributable to data centers in ai.

We are spending as much on AI and data centers as the GDP of Singapore. And AI is generating enough revenue to represent the GDP of Somalia. Um, so there's a big discrepancy.

There's a canyon there, right? But speaking of ROI, yes. Speaking of roi, so, but nevertheless, it's damn the torpedoes.

Full speed ahead. We're building data centers, baby data center, baby data center. Kimberly, what, what's going on?

Well, there has been some, a bit of reporting about the next generation of data centers being underwater. Although we've talked about this for decades now, about the underwater kind of stuff. I think we're gonna go back to Atlantis or whatever we wanna do, um, or putting it on the moon or putting it in orbit or whatever.

You know, maybe it's, you know, feral is, doesn't even exist or something. It's, it's in our imagination. But, um, there's been a bunch of people that have been, um, experimenting with these areas.

Like Microsoft. There's a firm, um, in China that is primarily a firm that has dealt with the, um, float floating, uh, flotilla out there, all the, the, the navies are, or the, um, the seagoing faring. And they're working on looking at putting data centers in underneath the water.

But so far, I think what Microsoft said the last time is probably 10 to 20 years from now. 0 and I think, you know, we'd be in like the seventh inning or something like that. So I think while it's really interesting what they're experimenting with, and they're, you know, getting some data back about what's potential, um, I think that stays in the same line as Elon's saying we're going to Mars.

Um, because there's a lot of physical, there's a lot of physics to be, you know, fixed, especially on, you know, that the, the, the, uh, five G's not gonna work, let's put it that way. And I, and 5G can't even work at my house because like right. Today we're having so much problems with it.

But the other piece to me that's really interesting is this energy and what's happening around the energy. It's, um, when you look at, you know, I just recently went through a, you know, another review on the investments and that kinda stuff. I'm taking a look at where we were in personally, where we were in terms of the energy infrastructure kind of technology and everything else.

And that is that that alternative part of AI has taken off like crazy just as much as Nvidia has. Um, and we've also, I've also looked at the atomic side of the house and the etf. The ETFs are in the atomic side.

They're a little bit more dynamic, I would say. But that is a market that's quite interesting. And we've got, you know, China's way ahead of us on the atomic energy for the, um, data centers.

And we're trying to catch up, you know, we've got approvals in Wyoming and approvals, I believe in, uh, in Washington state. But that's kind of where it's going. You know, we, we've gotta focus here and now to deliver what we can, at least in my my age, by that time they get into the ocean, I think I'll be dead.

Yeah. Well, they, they were talking about putting them up above the Arctic circle, you know, to take advantage of the, uh, cold weather. But of course, with climate change, it's not as cold up there.

And, and so you don't, you don't hear 'em going up there too much, but, but let's melt some more ice. Right? But, but Kimberly, you know, you, you bring up some very interesting points.

You know, if you, the book the Goal, and then of course the Phoenix project that's been been on it, you know, the theory of constraints, one bottleneck leads to another, right? Certainly we could put up buildings in West Texas, in Abilene, and out that way and, and in some of the states that are leading, and, and we, and we are Alan, yeah, we are. No, they're building, they're building, they're building big data centers.

You could build big data centers, but you gotta power those big data centers and Yep. Power and water, those two things. Well, if you using right, if you're using water to cool and, and you have to do some liquid cooling, there's a question of whether you use water or other liquids, but yes, water and, and power.

And so when you look at this, you've got an administration that is, is making it harder to use renewable energies like solar and, and wind. So they are forcing you to use nuclear. And, and I'm all for it, more nuclear usage.

But that, that's a window, Kimberly, to your point about being underwater, when was the last time we brought a new nuclear facility on in this country, right? It it, you you're talking measuring that in years. In years.

Yeah. Decades. Decades.

But so then what are you left with? Liquid natural gas, Kevin ding, big coal, and you wanna build them in Texas the last time, and Robert, no disrespect, but the last time I checked, Texas wasn't known for their redundant uber re resourceful electric grid. Oh, that's right.

That's, that's why they need the power. And they also need access to be able to run generators on LNG. So where is there a ton of LNG?

Where is there a ton of renewables? Like for example, in West Texas after nine o'clock, electricity's free. They, they just say, oh, run your dryers, you know, But, but it's done with solar and wind.

Yeah. Well, don't, don't tell the government here, but yes, yes. It, it's happening.

And because it's cheaper, even with, um, the difference in structure with, with, uh, you know, writing down your investment in, uh, you know, you know, hydrocarbons versus solar and wind, you can do it immediately with hydrocarbons, with solar and wind. You have to do it over the lifetime of that investment, the lifetime of the turbine or of the, uh, you know, uh, uh, of your solar panel installation. Even with that, it's still turning out to be cheaper and they're generating an excess of it, uh, an excess of energy.

I think you need a combination. You need, you know, your hydrocarbons, you need wind, you need solar, you need hydro, whether that's, you know, a river or waves or whatever. And so, but the easiest one right now is LNG.

There, there's currently a surplus. And if you build it in Texas, like around, you know, Midland, Odessa, Abilene, um, my, my Texas accent comes out when I say those, those city's names, sorry. But if you build it there, those providers of l and g are like, oh, well it's a lot cheaper.

We'll, we'll just, you know, top off your tank here. And so as we move to underwater, as We move to Robert, wait a minute, I, I gotta, I gotta inject here. It's cheaper today because they have an excess.

If you start building 3, 4, 5 data centers, there isn't gonna be any LNG excess. And you're gonna start seeing prices, not, not the data centers, 'cause they'll handle it, but people will start seeing prices Increase. Well, you're already seeing it in places like Ohio.

Yeah. Where they're building a lot of data centers. Well, sure.

And, and, and that such is the way of, of, you know, the market supply demand curves. Yeah. Yeah.

But people are making these decisions today. Right now, and, and I just know this because, and, and I, I get to do the other Texas thing. My, my daddy's in oil and gas, and he's got a lot of friends and colleagues that, um, you know, for their ranches and their yards that they run their businesses out of.

People want to build data centers there because they have access to l and g, they have mineral rights and they've got water rights, and it's big. And it, there's a ton of power generation that's going on in south Texas and West Texas. Uh, people are building them, you know, know, and you're, you're right.

You know, Jack, it, it is gonna change, but for where it is today, that's where they're going. So I'll, yeah, I'll, I'll point out that Kimberly sent out something earlier to the group about where the new data centers are being built, and the, the number one state that's getting all of these new data centers is actually Virginia. And, uh, my parents live outside of Manassas where all of these data centers are being built now.

They're being built there. One, because of the amount of high-speed internet that's available because of the US government, and two, because it's a lot of fed ram and US government data going in the data centers among other things. The downside is they are incredibly noisy.

The fan noise to cool them is really obnoxious and loud. The transformer hum is very loud. They take up a tremendous amount of space and they employ very few people.

Right. Which is why it's a good thing to put it in Texas, because there's nobody there in the middle of, in the west Texas states. Exactly.

You want them out The middle. Absolutely. Country.

The cows don't care. Yeah. But then, but, but so I, No Cows West Texas, Mohamed, come, wait, ham can come to the mountain, or the mountain can come to ham.

The reason they're going into North Virginia is because you already have a hub. It's already the biggest data center concentration in the world, probably. And you already have Jack, as you mentioned, the high speed connections and the infrastructure in place for that.

You now, look, my, my youngest son was a TV Robert, you know, this was a TV sportscaster in Abilene, Texas. I've been out to Abilene, Texas number of times wind turbines as far as the eye could see, right? You heading into town, but you go and, and you go look at the, there's a, a Stargate project data center complex going up there.

I think it's three to five buildings. Three to five different data centers. com days.

Millions, Tyson's corner. Mm-hmm. Right.

Million. We are talking mega factories. They're, they wanna build AI data centers the size of Manhattan in Louisiana.

Yeah. Yeah. It makes Walmart superstore look like a, A community store, like a small, like a small mom and pop store.

You're talking bodega huge, Huge facilities that are gonna suck. You know, that giant sucking noise, you hear it's the water and power going in to run these things. But, but here's the other part of my shimmy says from last Thursday, set to the tune of Led Zeppelin when the levee breaks.

Yeah. What are you gonna do when the AI bubble breaks Ron? Because make no mistake this, I love ai.

I am not saying it's not valuable and it's not revolutionary and it's everything else. So was the internet in 1999? And you know what people were telling me in 1999 and 2000, don't worry.

It's a new paradigm. It's a new normal. It's the new reality.

It's the way things are now. It's the same crap I'm hearing today from people who were in high school in 1999. Okay?

Remember a OL? Yes. Well, I, the Tysons data center that we operated, we, we bought from a OL but in any event, when the dotcom bubble crashed, we all of a sudden the term dark fiber became everyone.

You, Kimberly, you know what dark fiber was, right? We all had, we all level three in these companies out in Colorado. And Interlochen, as far as the eye could see, there were storage and, and bandwidth companies, right?

com era. My belief is it's gonna take 10 years or maybe more for us to fill up these monster AI factories that are being built right now. And to use the power, it may take 10 years for that power to come online if we're gonna go nuclear.

But, you know, to the, the power that we're talking about, you know, power generation that we're talking about building in here, if this thing goes south. 'cause after all, it still is Somalia in terms of revenue. That's what we're looking at.

And someone's going to get look quite holding that back. It could be even worse. Alan, I, I, I'm suspecting, you know, a lot of people are putting up these buildings assuming that they're gonna be able to fill them with data centers.

I disagree with that completely. They are. These people are building based on existing contracts.

They are building. You will note that the entire discussion is not based on square footage, but is based on energy units gigawatts of energy. And in fact, if you notice the last Nvidia a MD deal reserved a MD processors based on energy, not CPU cycles.

Right? I understand. Right?

So no, I fully understand That. It's, it's if you have the energy available today, people will put computers there today. But Jack, at the end of the day, if it don't make money, right?

Yes, but I, but I is, But I understand that. I don't disagree with you, but I'm simply saying that, that the, the building boom of data centers is not speculative in nature In terms of Oh, it absolutely is. Oh, no, no, no.

Where, lemme ask you a question. Where is OpenAI getting the $300 billion to build these data centers? That's not speculative.

So I think it's A circular, it's a Kimberly that Think a circle jerk. I I, There's two sides to this piece, guys. I mean, you're absolutely right on the, where's the, the revenue, the real revenue coming from, which is the enterprise.

Kind of a goodness that I saw with Dell had a financial analyst day this last week and last week, and it was one of the things that they highlighted was how many new customers they have that are buying AI processors. Now that could be equivalent to how many people were buying Cisco and all that kind of stuff and, and Sun back in 1999. So yes, I would agree that that's part of it.

But you know, we look, I look at these big data centers and these are the ones that are gonna be driving the tokens and that kind of thing. And then you have the implementation of what's happening in prem. And that goes back to what we just talked about in the prior block, which was the, the agentic.

And how do I, you know, move that faster to the development of there, because I think we have seen that there is value proposition in doing what's going on. You know, there is a big value proposition. com and a zillion other companies that were going up on the internet.

This is real companies that make, already make real money and are delivering product, automating their systems internally. com, whatever. Boom.

So I think there's, there's a difference here, and I agree with you. We're, we're in for a crash. We are definitely in for some sort of crash that's gonna happen.

But it's a different, is somewhat of a different basis of economy in terms of where this is going. Yeah, but you gotta look at it, you gotta look out 2, 3, 4 years, right? A a and if you look out three or four years, most of the agents, most of the agent ai, most of ai, probably 80% of AI is gonna be running at a local distributed level.

Not in these huge cloud-based data centers. It's gonna be running on-prem, it's gonna be running on your PC on The edge. Yes.

It's gonna be, it's gonna be 80% of, we're estimating 80% of AI workloads in two to three years. But I, I think it depends, it depends how big, how big this is, Kimberly. You're right.

The companies that are using it now will use it more. But you know, a lot of the articles I read is the real success of AI isn't gonna be on how well Google and Microsoft and Meta do it. It's gonna be on these next generation AI companies, the neo clouds, the, the robotics, the, the everything else that is good because what we are spending for, and make no mistake, we're, we're spending a trillion dollars or a trillion and a half dollars on data centers to, to house this AI boom.

It's a trillion to a trillion and a half dollars with a T. And By the way, Alan, that's just in the us. Yes.

Right? I think a trillion and a half might be Europe too, but whatever, let's not quibble over a couple hundred billion. Um, but, you know, to justify that kind of investment, what's the Kimberly's point?

What's the ROI, right? What's the ROI you need, I mean, you know, you talk to VCs, they always work on 10 x, right? I need $10 trillion.

That means 10 to $15 trillion, Right? Right now I'm at 19 billion in Somalia fighting war lords. That's, Well, Alan, that's because with the VCs, only one of those 10 companies actually makes it so they have to do 10 X.

Well, that, that, that's their model. But that, that was another point. com bubble was built on VC money and debt.

What's fueled a lot of this data center boom is CapEx, CapEx by the Mag seven. These companies were sitting on literally hundreds of billions of dollars. And they are, you know, I don't, I I I assume some of 'em are keeping dry powder, but they're all in, they're, they're using their reserves to, because it's a FOMO situation.

Microsoft's not gonna let Google win out. Google's not gonna let AWS win out. Apple's not sure what they're doing, but they know they gotta do something, right?

So there's an interesting twist on the CapEx story too, which is the recent changes in the tax laws mean that organizations can take a hundred percent of their CapEx against their taxes in year zero. They don't have to depreciate this CapEx, which means you're gonna see that's part of this as you're seeing a big shift from opex into back into CapEx because of this. Yeah.

And you know, and then don't worry, the middle class will pay their taxes. We'll wake up for it. And, and by the way, you know, all of these numbers that people are throwing out, you know, the Stargate five, what, 500 billion, a trillion dollars over 10 years.

Anybody that says I'm gonna spend this amount of money over 10 years, I, I take with a very, very large grain of salt. No one knows what they're gonna be spending three years from now, let alone 10 years from now. Yes.

So is all of that actually gonna be spent? Probably not, you know, we'll go somewhere else. A lot of this number is, this is really fuzzy stuff that we're talking about right now.

And and are you talking Are talking about voodoo economics? No, I wouldn't do that. Okay.

But yeah, I, you know, No, there's no doubt about it. But you know, Kimberly, I think you know it. I know it.

I think all of us know it. There's going to be a correction here. Yeah.

There has to be. Yeah. Doesn't make AI bad, doesn't make AI not useful.

It's just maybe we're out ahead of our skis in, in, in what we're, we're pledging and spending what was, what was Alan Greenspan's term? Irrational exuberance. Irrational, exuberant.

There's probably a little irrational exuberance set in. But guys, I gotta pull the plug on our irrational exuberance to discuss this today because we, we've gotta get on with it. We've got Text Drunk TV coming up here.

Um, Jack and Jack, pair of jacks at least, but you're not one eye jacks, uh, we've got a pair of jacks. Kimberly, Robert, thanks for joining us. Thank you for watching.

Again. We've got Text Drunk TV following this. It's Monday, guys.

We got a big week ahead of us. We'll be here every day of it. You'll watch Texture on Gang.

We're out.