First Trust ROI Podcast
On the ROI podcast, we discuss some of the most important questions facing investment professionals today, ranging from macroeconomic views, to perspectives on the equity and fixed income markets, to insights on practice management. We aim to cut through the noise, examine the data, and provide fresh insights to investment professionals as they help their clients find better ways to invest…seeking to generate attractive returns on their investments.
First Trust ROI Podcast
Ep 53 | Brian Comiskey | How are Technologies Evolving into Digital Utilities?| ROI Podcast
Brian Comiskey, Senior Director of Innovation and Trends at the Consumer Technology Association (CTA), explores how emerging technologies—including cybersecurity, AI, robotics, and cloud computing—are evolving into digital utilities, with important implications for investors.
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Hi, welcome to this episode of the First Trust ROI podcast. I'm Ryan Isakainen, etf strategist at First Trust. Today I'm joined by Brian Komsky, senior Director of Innovation and Trends at the Consumer Technology Association. Brian is an expert on technology and that's what we're going to discuss. We'll talk about cybersecurity, robotics, artificial intelligence, cloud computing and a variety of other topics. Thanks for joining us. So, looking around the world, there's quite a bit of stress, there's quite a bit of conflict, and one of the things that strikes me is that the new frontier of war isn't necessarily kinetic war, but more information and cyber war, a lot of potential cyber threats from some of the players on the geopolitical stage. So my question for you, brian, is, as you kind of think about cybersecurity quite a bit and some of the related technologies, how do you expect that will actually impact spending on cybersecurity from companies, from nations? Do you think that'll have an impact?
Brian:Certainly, and part of the experience that I like to draw upon and think about is I used to do some consulting with the US Coast Guard, and one of the areas that was a major focus of my time there was building out new policies around cybersecurity and cyber operations, because they recognized that we were moving from three traditional theaters or kinetic theaters of war, land, sea and air into a fourth theater that was equally important, which was the cyberspace, and so you already saw that investment going in from the US government side, and that's something that's definitely replicated throughout the world, where you're seeing budgets increase in the EU, you're seeing those budgets increase in APAC region, and so certainly governments are recognizing that they need to play a role in amping up cybersecurity from the idea that there are nation states that might attack them in that regard.
Brian:But one of my favorite stats is only 25% of cyber attacks are state sponsored. Most of them about 75% are financially motivated, which means that they're not necessarily targeting a nation state. They might be targeting a business in this case, and if it's such a lucrative illicit economy that emerges, then companies need to make sure that they're spending in order to protect from themselves against it. So we expect about like $212 billion in information security spending this year alone per Gartner.
Ryan:So is that ransomware sort of attacks? What's the financial motive when you're talking about financial motives, is it ransomware? Is it corporate espionage? What sort of financial motives are we talking about?
Brian:It can be a bit of both Corporate espionage, for sure but that usually means that you've got to pull back a layer and there might be a nation state behind that. But usually it's ransomware which has a lot of payments. And if you look at the stats going in from 2023 to 2024, you saw a 5x increase in the medium ransomware payout, which, when we think about what those payouts look like, it's not just oh, here's the money that I'm spending in millions of dollars to get my data back, but you've had an impact to your operations as a business, which means, uh-oh, I have more costs that are associated with it. So when you think about paying out ransomware, it's not actually just a one-time only payment. It's usually a three-year cost window that you're paying out, where you're paying 66% of your total cost from the impact the first year and then another 22% second year, and then you finish out with that 11% in your third year.
Ryan:So explain that a little bit more. The cost is spread out because the cyber criminals come back and say, okay, you paid me once, you need to pay me again. Or am I missing something?
Brian:It's more about the cost and impact of operations when you're losing all that opportunity costs.
Brian:Opportunity costs and that's one of the most important things where a lot of companies are considering. They're like, well, what if I just have backups right, like I can beat the hackers? I can beat people. We're going to try and hold my data ransom by having more and more data in different storage areas, in different off premise orpremise or in maybe different cloud environments. But those hackers are getting smarter, which means that they're targeting backups more and more. That's one of the weeding trends that we're seeing. So what that does is it holds companies to account, saying that you actually need to make sure that you're budgeting for cybersecurity in this instance, because it's really a requirement for basically modern enterprise operation.
Ryan:Yeah, you can't afford to not spend, yeah, so what's? We've talked about this before, but if you could discuss a little bit more on the linkage between cybersecurity and the need for cybersecurity and sort of this new frontier of artificial intelligence, how are they linked?
Brian:Oh, they're certainly linked. I mean, I think a lot of it is. Cybersecurity's threat landscape is already under constant evolution. It's always changing. That's where solutions have had to meet and match up to it. But what artificial intelligence does is rapidly increase that evolution timeline and lifecycle.
Brian:So when we think about what artificial intelligence does, it increases the speed of ransomware attacks. We've seen an 1800 or so percent increase in distributed denial of service attacks. That's usually bot generated and we even see the idea that phishing attacks which usually you know it when you see it right, when you get a bad email, you can tell that this isn't addressed to me those emails are getting a lot more sophisticated. If you haven't noticed that this isn't addressed to me, those emails are getting a lot more sophisticated, if you haven't noticed, and a lot of that is it's turning large-scale phishing attacks into spear phishing, which means they're much more targeted to the individual. So you have a threat landscape for artificial that is driven by artificial intelligence that is getting much more complex and rapid. And if you look at that from the negative side, what does that mean? In terms of the positive side? Well, you can leverage artificial intelligence towards maybe being better at automated threat response in particular.
Ryan:So there's both sort of two sides of that AI coin when it comes to its relationship to cybersecurity. You've got the cybercrime side, where they're getting more efficient and better at their jobs, and then the response is also getting better by using similar types of resources.
Brian:Exactly Like in anything in cybersecurity space, there's always what you would call red team or blue team. Right, the red team that's engaging in the hacking activity, blue team is your defensive unit. Well, in this case, you're probably seeing a future where artificial intelligence leads to red teams being made of bots and blue teams being made of bots in return, which then effectively helps if you're defending against an attack. Triaging you get, so that your human resources, which are limited, because if you were to take every single certified professional in the world and try to fill out every position, you'd only fill two-thirds of them. That's how much of a gap there is in terms of qualified professionals on the cyber front. So you really need those automated detection units, and there's companies like CrowdStrike, sentinel One, darktrace, that are really good at these automated threat responses. They're very much AI first cybersecurity companies at this stage, and so what that does is it allows you to triage effectively down so that your human responders can respond to the major breakthroughs and breaches that require a little bit more of that human creativity side.
Ryan:One of the things that I've begun to hear a little bit more about and I think most agree that it's still on. Think of the relationship between quantum computing and cryptography and the ability to protect, you know, digital assets. As a result of that, If you can crack someone's password almost instantaneously, all of a sudden the digital world that we live in becomes a very dangerous place. So what's kind of coming on the horizon related to quantum computing and cybersecurity?
Brian:Yeah, and we're talking about quantum computing. It feels like it's very far away and, let's be honest, commercially viable. Quantum computers in terms of being widespread and in use is probably a 2030s innovation. But if you're going to be a savvy business or savvy government in in this case too right, because we're talking about there's interest in increased spend by governments as well as enterprises you have to start thinking about now what the quantum landscape looks like. Quantum computing can really break through traditional encryption quite fast and quite easily. So what you have to start doing is build what's called post quantum cryptography. So how do you start building and planning for that future? Well, that's already happening right now.
Brian:There's contests from groups like the National Institutes of Standards and Technology that are really asking for companies to put forward tools that can build and reflect this quantum future. How do they do that? Well, oftentimes they're using simulated quantum environments that use a cloud infrastructure. So think like AWS or Azure, and you can use AI to actually simulate a quantum environment. And while this sounds like it's far off, they've already found two companies that have actually been able to meet some post-quantum cryptography standards. So you're already seeing some of the solutions be built now, which should be a sigh of relief for a lot of people Because, again, the 2030s are coming sooner than we think. We're already halfway into the 2020s, so we'll be at a time of quantum computers faster than we know it.
Ryan:Yeah, I've heard stories and you can maybe tell me if this is actually happening or if maybe I'm worried about nothing happening, or if maybe I'm worried about nothing, of cyber criminals actually getting a hold of data that is protected. It's encrypted data With the thought of later on, once I've got quantum, I can break that code and actually have access to the data. So, even though you have encrypted data that maybe even a nation is stealing to store for later, once they have access to that quantum computing, is that something that's actually happening or am I worried about nothing?
Brian:I would imagine that's probably a strategy that people are deploying, so I don't think it's a worry out for nothing Seems like a good.
Ryan:hopefully I haven't given all the cyber criminals good ideas now on this podcast.
Brian:That is a pretty good idea. Maybe you have a side career that I don't know about.
Ryan:Okay. So the bottom line is we're at a point now where every company, every government agency, individuals everyone needs this as a product or service, and it seems to me that the spending has become non-discretionary in this and your CTA. You guys have come up with a really good term. You call it digital utilities. Can you talk a bit about why you call it digital utilities?
Brian:Yeah, of course. So we view cybersecurity, cloud computing and AI robotics as the new digital utilities. So the way that we view it is like water or electricity that are required. Say, you want to open a business, you sure want running water and electricity to power your building and allow for good facilities, right? Well, in this case, we view cybersecurity, cloud and AI as all being part of this new wave of digital utilities, which are requirements for any modern enterprise to operate in an increasingly digital world. So what they offer are what we would say are three S's Security, straightforward, right?
Brian:You want to make sure that your data is secure, that your operations are operating in a way that's not going to be hacked anytime soon. Cloud offers scalability the ability of, say, a small business to have greater reach through e-commerce tools, having cloud infrastructure to host all of their data from all of their not just their customers, but also their employees. And the last one is AI and robotics offer simulation. We produce so much data on a day-to-day basis about 1.7 quintillion bytes, which is 1.7, followed by 18 zeros, which is a number that's very hard to fathom. Seems like a lot of data. Seems like a lot of data. Seems like a lot of data and it's impossible for humans to be able to process on a given basis. So you want AI robotics to simulate human productivity as much as you can. So security, scalability and simulation Okay.
Ryan:So the CTA, that's, the Consumer Technology Association, is, I believe, the largest trade group for technology in North America. Is that correct? That's correct. You put on the Consumer Electronics Show, or the CES. Yep Is what it's called now, yep the.
Brian:CES because about 40% of our exhibitors are doing enterprise products.
Ryan:So it's no longer just consumer.
Brian:It's not just consumer and if you think about that, that line's been blurring for a long time. This idea of well, an innovation in the enterprise will come to consumers. I think 5G in particular, where it was adopted by businesses for rapid scale deployment of digital operations. Then it really came to your phones and got better connectivity over time. That's one example of it, but sometimes it might go the other way. Where smart glasses, for example, you have meta-ray bands that are quite popular with consumers. Well, there's enterprise applications in the long run, like augmented reality on glasses, helping surgical applications. So it might be where you see the popularization in the consumer landscape actually influence the enterprise. So that line only got blurred, I think, more during the pandemic, where you had work from home tools, so common consumer device, like an earbuds or AirPods, anything that you can think of. Well, those are also work devices now, because it's how many people are taking calls on them and using them as an enterprise product. So it's really nice to be at the nexus of it all at CES.
Ryan:And CTA has an index, a thematic index program, which is why we have First Trust, has a relationship with CTA and NASDAQ, who create some of the indexes that our funds track, and for First Trust, one of the things that's really valuable in that relationship is sort of the edge that you have in understanding technology and understanding some of the companies. So could you talk a little bit about that, the edge that you have at somebody who's very close to the technology industry? How does that make you better able to identify companies that might make it into one of these indexes?
Brian:Yeah, well, I think it comes with some of it is the Roots for our trade association. So we represent over 1200 members, so we have this ability to see companies from your large hyperscalers, your Amazon, google's, but the majority of our membership overwhelming, like around 80% are startups and small businesses, so we see that early stage ideations of new technologies occur, so that's allows us to see the entire technology lifecycle. You have CES, which is a global show. About 40% of our attendees are actually from abroad, so they're from APAC Europe. Across the board. We're able to not hold to just being a North American trade association. We can take a very global view to innovation, which I think is quite important when you think about how technology diffuses across the world. But then I think one of the most important things about this and this is why we love having our partnership with NASDAQ when we develop indexes NASDAQ is an incredible institution when it comes to finance and quantitative measures.
Brian:They've been doing the index business. They've been doing the financial business for decades. We let them focus on that. That's their expertise which allows us and frees us as a team myself included to focus on the technology itself and really spend our time looking at patent portfolios, research and development budgets, merger and acquisition activity in the tech field. Or our big one is calculating thematic revenue, which is, how much revenue do you derive from a given theme? That's usually a pretty intensive manual calculation because you're having a human comb through financial statements and take their expertise of a technology and say, okay, this is how much they get from cybersecurity or this is how much they get from robotics. So I think that's really what sets it up is we can lean on the partnership at the end of the day to let us be CTA and be technology experts.
Ryan:Yeah, so you're not. I'll paraphrase what I just heard you say you're not necessarily just looking at the financial statements, but there's a little bit more. There is the quantitative aspect to it, but there's also a qualitative understanding of the companies.
Brian:Is that fair? Exactly, I think that's a very fair assessment. I think qualitative is really where our bread and butter is. It's what we're leaning into.
Ryan:Okay, so we've talked a bit about cybersecurity. I want to talk a little bit about what everyone's been talking about over the last couple of years, and that's artificial intelligence, and again we touched on it a bit. But as you kind of look at what's coming down the road over the next year or two, what is it that you find to be kind of most exciting about AI?
Brian:Yeah, well, I think there's really three frontiers of AI innovation that I'm excited about. The first is agentic AI. So when we think about agents, right, these are basically AI bots that can execute a task for you with minimal or zero oversight. So they can move, say, a new hire right into your payroll, your talent retention, without you having to continuously move all their data from app to app to app. That's pretty revolutionary, because, as great as the app economy is, it can be pretty inefficient at times if you have to constantly move data from silo to silo. Well, what if an agent can do that for me? That's the first one.
Brian:Digital twins is the second one that really excites me, where the idea that you can virtualize an object into a digital environment and do AI-based simulation and scenario generation means that if you're limited on budget, you don't have to sacrifice your research and development potential. That's the second one. And then the third one is physical AI, which would basically mean robotics. How do AI algorithms placed on robots really allow for turning it from being hard-coded? Input A, output B to input A of this algorithm allows for outputs B through infinity. So those are the three pathways I see, and I can talk about any one that you want to go with, but those are the three. I think that excite me the most.
Ryan:Yeah, People that I spoke with coming out of the most recent CES in Las Vegas earlier. Well, I guess it was the end of last year, the beginning of this year.
Brian:Beginning of this year.
Ryan:It's always in January, okay so one of the things that I heard repeatedly was people were really excited about some of the robotic applications and you know just some really cool stuff that was going on there. Let me push back on that for a second, and I maybe I'm just a bit paranoid about having a humanoid robot roaming around my house, so set my mind at ease. Why is that a? You know whether it's Optimist or one of these other robotic companies. You know why should I be more optimistic than I am? And maybe I'm just I grew up watching the Terminator and you know RoboCop and some of that, so set my mind at ease.
Brian:Yeah, I think a lot of it is. It first starts in the enterprise. So I think, like, let's start with where it's occurring. It's occurring in warehouses, it's occurring in the medical sector, it's occurring in the hospitality sector, where you have humanoid robots, in particular, being designed to fill workforce shortages, so it's helping make things more efficient. So, especially if you're thinking about warehouse workers moving packages that you might want delivered, if you enjoy that two day delivery, this is how we keep that in place by having those workforce gaps met. So that's the first one, I think.
Brian:On the consumer side, I think one of the big areas to think about is aging populations. Who's going to need a consumer side humanoid robot first? Well, it might be as a caregiving. We saw that actually at CES this year. There was a startup out of France that focused on building humanoid robots that were actually anime design inspired, so something a little bit different than trying to make it look like an artificial human, to go with something a little bit more friendly, a little bit more cartoonish, because they're trying to put the mind at ease of the potential people that they're taking care of. And, as more Americans in particular, and as we found age, they rely on technology increasingly like they view smart doorbells as healthcare products, because it's an emergency camera system and it can also alert people to when they're you know they need something more than they are currently getting with their caregiving situation.
Ryan:So is there a really good reason that some of the robotic applications would have that sort of humanoid form factor? I mean, I'm perfectly comfortable to have a Roomba roaming around or vacuuming my house, but I mean, does it have to walk on two legs and have arms? I mean, does it have to walk on two legs and have arms? And you know, it seems like a robot or some sort of robotic application could do these things without necessarily looking or having the form of a human.
Brian:It's certainly possible, and there's companies like Rich Tech Robotics that come to mind from the show four, where they build mostly like they have one that has arms and it looks like a kind of like a star wars-esque. Uh, bartender droid, it's called adam it works at the texas rangers ballpark.
Brian:It's not quite human, but the arm movements aren't completely human, because if you're gonna have a robotic bartender, you really want to make sure that it's simulating the human motion as best it can. So of course, the joints are going to resemble that in particular, but they have service sector and hospitality sector robots that look more kind of on the r2d2 side, where it's just carrying trays or it has arms, but it's a moving like kind of a tin can in a little bit um, and so I think it doesn't necessarily always need to be human-esque in the performance. It's just how can you simulate something that we expect it to be human-like? And so you say you're comfortable with Roomba. Well, we saw from Roborock, a competitor of Roomba, them developing vacuums with arms on boards so that the arm can move objects out of the way more efficiently, and so which is exactly what a human would do in this case, because sometimes I think in the past we go well, I can just do it.
Brian:This is sometimes something that I find myself saying, where I'm like I can do that better yeah like I can vacuum and I'm gonna get exactly what I want done the way I want it done, because I have to move the cord out of the way, I have to move all these things, yeah, um, out of it. But you put an arm on a robotic vacuum and now you're actually like, oh, it can actually compete with me quite well and I would.
Ryan:I would think maybe having a little bit more intelligence in that vacuum could help it understand, because, quite honestly, my Roomba usually gets lost and we find it in the laundry room and it's kind of stranded a few days later Like where is the Roomba? And sure enough, it's gotten lost somewhere. So I do think having some form of intelligence paired with these robots would be an important step.
Brian:You have to. And that's where that term physical AI, which was introduced on stage at CES by Jensen Wong during his keynote this past January, really comes into mind, where robotics are increasingly just the physical embodiment of AI algorithms and I think the Roomba example getting lost is a good one. I tend to think about what it can mean in the medical sector. So companies like Johnson Johnson, stryker and Intuitive Surgical they've been using robots for joint replacements and other applications for years. Well, even though it sounds like a rinse and repeat process a knee is a knee, a hip is a hip that's not really quite true. Every person's knee is different than than others. Every joint is individually made. So if you have an AI algorithm that can better scan and understand what's going on on board with the individual patient, that robot becomes a lot more catered for what would be personalized medicine, which fits very well into this longevity and the overall healthcare theme that's going on right now too.
Ryan:Yeah, it seems like there's a lot of linkages between AI and healthcare. The examples that you just gave, or maybe I've heard examples of surgery related to cancer or something and making sure using AI to somehow make sure that you've got clear margins when you're removing a tumor or something like that, instead of just relying on just, maybe, human input, a higher success rate using AI. Is that something else that you see?
Brian:Certainly, I think healthcare is probably one of the best beneficiaries of AI in general. There's a company called Tempest AI that I think of a lot, where they're using AI for diagnosis, diagnostics as well as drug discovery. So them and Illumina are two companies that are really leaned into the AI story to really push forward where the healthcare sector can go.
Ryan:You mentioned digital twins a minute ago and that makes me think of all the different industrial applications and construction applications, and it just seems like that is a huge set of opportunities. If you can virtualize something and do this sort of digital twin work. It seems like it would add some productivity and some efficiency. So can you talk a bit about that?
Brian:Yeah, of course, and so when we think about digital twin, again, this is a digital representation of it can be a physical object, it can be an environment, it can be the entire earth, like NVIDIA has done. It can even just be a process that you're visualizing. So how does a factory floor operation move across the board? What it really does is unlock opportunity to save on physical capital expenditure, to start better planning your allocation of your resources. So a company that comes to mind is actually someone like Siemens, who they've done and they've partnered on the industrial applications, the construction side. One of my favorite examples, though, is that they actually create digital twins for the Red Bull racing Formula One car.
Brian:So in Formula One, there's a cost cap. You can only spend so much on innovation in a given, or so much in a given year. That includes how much goes into the development of the car. Well, if you're in that mentality, you might start cutting corners on how much you're putting into aerodynamic testing or the like. Well, in a digital twin environment, what they do is they take sensors that are on the car at all times, that feed back into the digital twin version so they can experiment and pilot for a fraction of the cost, exactly what they want to do and changes they want to make in the car.
Brian:So it creates this virtuous cycle of innovation where the digital car is informing the physical car, which has sensors feeding back to the digital version of the car. And that's just one element. There's a healthcare story too there, where companies like Dassault can do it on the human heart, which allows medical researchers that maybe might have their budgets not be quite what they used to be. Right now they can use a digital twin of the heart to practice surgery over and over again, because you can't really test on a cadaver only so many times. And they have found they've actually pioneered some new pediatric cardiology surgery techniques that have saved a few thousand lives already.
Ryan:It strikes me that that is basically kind of like a really complex video game, yeah, and the background of a lot of this is actually in video game development, yeah, which is, you know, I think, is kind. Of. I don't know if it's surprising, but it, you know, growing up we were always told, like, video games are, you know, a waste of time or something like that. But, as it turns out, the same sort of technology that was really invested in because of video games is what has, it seems like down the road, resulted in some of the AI that we're seeing today.
Brian:Yeah, some of the stuff that you're seeing, like Epic's Unreal Engine, some of the stuff that you're seeing from Unity Technologies in particular, they really start to, I think, improve the virtualization field in a way that we haven't quite seen. And what's really cool that you mentioned is Siemens. The person that they partner with on a lot of the visualizations is Sony, the maker of the PlayStation, so it's not surprising that gaming expertise is being leveraged for these high fidelity versions. Visualizations you go to gaming, I think of every time. I always go to like something like iron man and how, when he first builds his iron man suit, he actually uses a digital twin in real time of moving out the mark pieces of the suit and in my mind I'm like that was 2008 when that movie came out, I think, and so we're already living in a future where that kind of exists to a degree.
Brian:You're just putting on a headset Interesting.
Ryan:Well, and then the other digital utility that you kind of linked in with this was cloud computing, and it seems like none of this would really be possible without that cloud ecosystem. Can you talk a little bit about that?
Brian:Yeah, I think in a lot of ways, we've talked so much about AI rightfully so but we overlook how important cloud computing is in terms of creating the infrastructure that enables us in the first place. When we think about AI what enables artificial intelligence we tend to go right to the silicon and the sensors. We go, okay, these are the most advanced chips and processing units, but think about chips almost as the brain. Data is the language through which those brains communicate. Well, who's infrastructuring that data? What's doing that? Well, that's cloud computing. So that is what your Amazons, your Googles, your Microsofts, your Oracles are all doing to try and enable this revolution, and we expect by 2030, based on AI demand alone that it will be about $2 trillion in spend on cloud or in terms of total revenue for the space. So this is a market We've been talking in billions for this entire podcast so far. Now we're mentioning trillions because that's where cloud computing sits in terms of its importance to enabling the revolution that we're seeing right now.
Ryan:Yeah, and all of the massive capital investments that have taken place. I mean, there's still plenty that will take place in data centers and all these huge complex warehouses full of GPUs and server farms and things like this, and all of that is operated by these cloud providers. Is that correct?
Brian:That is correct, and then they're also making deals directly with some other companies that help support GPU compute as a service.
Brian:So something that we've been watching really closely is how does a company like CoreWeave, who has deals with NVIDIA, start to better partner with some of the cloud providers in terms of dialing up that compute as a service overall? And so one of the questions that we're financially asking is is that more of a software as a service or is it actually closer to something like an infrastructure as a service where it's really pioneering, allowing for the operation of the cloud as a whole? Probably right now I'd lean more to software as a service, but ask me in a few months and maybe that shift changes as we start to really understand how the layers of cloud are evolving alongside AI, because that's the thing we tend to think about with cloud, and why I feel sometimes it gets overlooked is, I think it gets treated as this static innovation, that it's not as important anymore, but it's vital, it's critical and it has to evolve alongside the needs and demands of data center, as well as power and energy demands.
Ryan:Yeah, and glad you brought that up, because I think that's another important point when we think about, whether it's robotics or all these things take electricity. They take a massive amount of power. All the data centers take a massive amount of power. And I'm just curious on your thought. I know you're not an energy guy per se, but how do you think, 10 years from now, how are we going to be able to scale up the power resources in order to provide enough electricity?
Brian:Well, it was funny, I actually did. My first clients when I first started my career were actually in nuclear energy and natural gas, and so what I find interesting is about that was over a decade ago. It was a very different conversation where the terms all of the above energy was not being used as frequently. It was a term that existed, but it wasn't used in the media as much.
Brian:And so what I find with the demands is you'll see a probably 135% increase in data center power demand from AI alone by the end of the decade, and so you've seen a lot of energy come on board from solar and wind, which are really incredible renewables, but working from the nuclear side. Nuclear is always on. It's higher in terms of energy density, so you need less uranium to produce as more in terms of terawatts of energy than solar and wind can do. But it's also costly and it takes time. So there's a few ways to do it.
Brian:I know this is something that you talked about a lot and it's and it makes me happy to see that this conversation is happening again which is you're seeing hyperscalers Microsoft, google and Amazon engaged in this capacity of saying well, can we just dial back on nuclear power plants that maybe have shut down, which there were a lot of closures a decade ago or so? There's not a lot more coming online. So we're trying to dial back on the power that we have now and we're trying to think about well, what does that look like in a decade from now? Well, there's a play of is it going to be these large power plants or is it going to be something like a small modular reactor, which there's a lot of patents for them? There's a lot of deals out there, but they're probably not commercially ready for another decade or so.
Brian:And that's just fission. There is the companies that are working towards fusion, which we've had some breakthroughs in from the Department of Energy a couple of years ago. With ignition, that workforce has increased by 200% in the private sector, so clearly that there's more interest than ever that maybe fusion's closer. I think fusion requires AI and quantum to get dialed up a bit more for it to become viable and it's probably something that's more of a 2040s technology. So what do you do in the interim? Well, it's probably an all of the above energy strategy of renewables, nuclear and, probably to a degree, gas in the mix.
Ryan:Yeah, it does seem like it's not something that we can wait until 2040 for the fusion technology that's always just on the horizon and we never quite get to and hopefully some of the breakthroughs that people have talked about become realized and they can actually. You know some of them. There's some pretty massive spending that's taking place to advance fusion technology around, you know, in Massachusetts and some other parts of the country, so that's encouraging. But you know to your point. I do think there has to be some spending over the next five years to actually increase the electricity capacity in the US to compete globally, especially with China.
Brian:Yeah, I think that's the biggest thing to focus on is really how do we build up this capacity and I think some of it too is. And what I find fascinating in this story was mentioning the hyperscalers making these deals themselves. We saw a shift with AI in general, with the headwinds that were in the merger and acquisition market where they couldn't really acquire as frequently in the last few years Companies across the board. They got into the investor mindset where Microsoft invested heavily into open AI. You saw Amazon heavily invest in AI companies. Well, now they're putting on a new hat, which is we're power purchasers, which I think is very fascinating. Which how does that translate into it? It might be a competition that's either driven by geopolitical competition or it might be just this is the table stakes and required for the future to bet on it. So it'll be a complex landscape for sure.
Ryan:It is complex and it adds a level of complexity and difference to the traditional asset-light business model of many technology companies. If they're having to make capital investments to a degree that they have never made before, that transforms the sort of business that they're operating, and so time will tell to see how that plays out financially and seeing what sort of return on investment these companies have with those capital investments. But I do think that they're kind of in a position where they don't have a choice. To some degree they have to make those investments if they want to be able to advance the technology and compete and have, if they want to be the winner in 10 years from now. Yeah, okay. Well, brian, this has been a great conversation. Appreciate you coming on the podcast again.
Ryan:I do have a final question for you. I want you to put on your you know futurist cap, okay, okay, so we've talked about a lot of different technologies. What is you kind of think forward, looking into the future, a decade? Is there any specific thing that we haven't talked about that you think is going to be? You know that maybe fewer people are focused on right now that, looking back a decade from now, we're going to say, wow, that was an amazing advance and amazing innovation and nobody really saw it coming.
Brian:I think it's one of the things that we talked about. I'm happy we already talked about robotics, quantum and nuclear, because those are the table stakes, ones that are quite popular. But I did mention one very briefly in the visualization, one which is, I think, smart glasses are oftentimes overlooked, where there's very few ideas, where you already had the start and stumble about a decade ago with smart glasses, of where they're going. But with AI capabilities on board, translation capabilities, augmented reality technology getting to a point where it's able to better be customized to a comfortable form factor that we're seeing, I think we might be in a decade seeing a point where there's a greater proliferation of smart glasses on the market than we expected, because I think it's the only device, by a form factor comparison, that might be able to compete with a smartphone.
Brian:I don't think it replaces the smartphone outright in a decade, but I think it's the only device that could possibly compete with it. In a way. It will come down to certainly looking at how many more models come on board. We're already seeing Oakley is now going to come out with their version to compete with Meta's Ray-Ban, or I should say complement Meta Ray-Bans, because Essilor Lungsotica owns all those brands, but I think that's one that gets a little bit overlooked, and I'm excited to see a lot more in terms of that innovation in a decade.
Ryan:So are those joint ventures typically that take place where it's, you know, the sunglasses company and the technology company are kind of working on a product together. Or do you see, you know, Apple or Meta or one of these companies trying to kind of put their own glasses out there?
Brian:I think right now they're leaning into the partnership approach, because part of when you get into something that has a consumer implication like that is you want it to look cool and I think, like I've seen meta Ray-Bans in the wild and they look like Ray-Bans, they look like a good sunglasses model. So I think that there's a lot of strength in that partnership approach. So, as much as it's going to be a technology that maybe redefines translation, communication and computing in different ways, it might also be a fashion statement which is pretty powerful in a lot of ways. So there's a cultural element to it which is important, because technology doesn't exist in a vacuum. It's adopted by people at the end of the day.
Ryan:That is a really interesting insight and we'll look forward to seeing your translation example. I think is really interesting, as somebody who travels internationally quite a bit, having the ability to have real-time translation coming from your glasses into your ear, instead of having to hold up a phone or something like that and say, you know, speak into this so I can get the translation. Yeah, that seems like a really interesting application.
Brian:Yeah, I think it would be useful. As someone who also travels internationally quite a bit I that is probably like the most in demand. As much as I love learning new languages, it's really hard, and so having something that can at least assist that and put that at ease is incredible.
Ryan:All right. Well, brian Komsky, thanks for joining us again on the First Trust ROI podcast, and thanks to you as well for joining us. We will see you next time.
