Artificial Intelligence: Energy requirements, Competitive landscape & more with Michael Lippert (Baron Capital)
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Hi everyone, Dan Cassidy here. Welcome back to the UBS Market Moves podcast channel. Our conversation today will revisit an investment theme which has been a top of mind for many market participants along with our Chief Investment Office here at UBS, that being AI, Artificial Intelligence. As this technology continues to wrap

evolve and influence markets. It, of course, helps to understand how we got to where we are today, where we stand today, and what the road ahead looks like. So to help us with that, very fortunate to be joined today here at our UBS studios in New York by a subject matter expert on this space, Mike Lippert from Barron Capital. Mike is a vice president, portfolio manager, and serves as head of technology research at Barron Capital. Just a quick

And I thank you enough for joining me here at the table here in the studio. Great to be with you and looking forward to our conversation today.

Thanks for inviting me. I'm looking forward to it, too. Let's go. Absolutely. So I suspect, Mike, many of our listeners, admittedly, myself included, are still in the process of learning about this rapidly evolving technology. Now, there seems to be a fair degree of complexities involved, and AI is quickly having

more of an impact on our day-to-day lives on a variety of fronts. So from your vantage point, what would you identify as being some common present-day AI use cases? In other words, how is AI currently impacting our lives? Yeah, I think we're just starting off. I mean, if you think about AI today, our listeners remember back to what the internet felt like in the mid-1990s, 14.4 modem. You were just starting.

Now, AI is moving much faster. I've never seen anything in technology. I've been doing it 25 years. I'm a history major in college, so I've studied history. There's nothing moving at the pace that AI is moving. I mean, just the chat GPT moment, you know, November of 22 is what, two and a half years ago. And just think of how the pace is.

Today, people already, as they're searching for information, they're trying to learn about a topic where they used to do a search. You'd get a number of blue links. You'd click on it. You'd read a webpage. You'd go to the next webpage. Now you just type it in. So, for example, this morning, one of the things I want to talk about with you is how much IT spending is – percentage of GDP is IT spending today. Okay.

big number bandied about. Just to remember every number, I did a search today on Grok, which competes with Chachi PT, owned by XAI Musk. I got the answer literally in two seconds. The other day when people were debating about what happened with the attack in Iran and whether or not the president had power, I'm a curious person. I just typed in a query about the war powers resolution, and I got a complete answer. I'm not going to get into it because I don't want to go into politics. So we have that.

In work, you are having today whether or not it is Copilot, which is the brand name of Microsoft that could summarize your emails or can write an email. The last time I wrote my quarterly letter, I was having a little bit of writer's block and I literally just pounded out a paragraph and I said, AI, help me make it better. I want it to be professional, but I want it to be a little colloquial. This is the style I want and how could you make this a little bit stronger?

It did. And now we are just in the first stage of what's called agentic AI, meaning an AI coworker that is literally helping you in your job. It could be like, I don't know much about this Mike Lippert guy. He writes quarterly letters. Summarize for me what he said about AI in his last four quarterly letters so that you know that. So AI can now do that for you. You just ask it and it could go do that rather than you doing it yourself or you assign it to a person.

The same thing will happen in our lives too. We're going to be able to ask an AI agent to plan a family vacation for us, give us some information, then book that. My kids like to swim with the dolphins. Book that for me. My wife and I want to go to this restaurant. We need a babysitter. And AI, very shortly, will be able to do all of these things.

So not necessarily apples to apples, but as far as what it feels like, what a search engine felt like maybe 20 years ago, as far as the impact, you have information right at your fingertips. And it's interesting, you pointed out ChatGPT a couple of years ago. Prior to that, I really had not heard about many use cases for AI. So it seemingly came out of nowhere. And as you've alluded to, it's moved so quickly only in the course of a couple of years.

So as we look further, let's just put a pin on it, say, the end of this decade. How do you see this technology, Mike, evolving from here? I believe that every single digital interaction that you have in your personal life, as a consumer, in your professional life, every single one will have AI as part of it.

When I first started talking about AI to people, I'd be like, remember every science fiction movie that you ever watched? The bad ones where the robots want to take us over? Space Odyssey. Space Odyssey. How? Was AI, right? And of course, we all know the Terminator, which my kids love. Skynet. Yeah. Or the good ones. How, you know, Star Trek, where you talk into something, computer, do this for me. All of that is because we knew that computing would one day get there.

And we are finally there now. But it burst on the scene to most people when ChatGPT came out, but it's been going on for a long time. It's been called something else called ML, machine learning. You know, for example, we had a meeting at Barron with Jensen Wang of NVIDIA back in 2018. And we spent the entire time talking about AI, ML, why NVIDIA is well positioned to do this.

That was full four years before the chat GPT moment. I looked the other day at the first note I had on AI. I was just curious. It was 2016 in our firm. But it took a long time to get there. So if you were an investor in 2016 or 2018, you were early. So we were early.

In the future, it will impact everything. I don't even think we can imagine what it will do. It will literally change society in a big way. Some positives. It will make us all much more efficient and productive. And some negatives because there will be jobs that you no longer need a person for.

And we, you know, in our society have to really think about these issues. So you think about the energy requirements needed to sustain this technology. It has to be substantial. How will this demand be achieved? It's going to be tough in this country because in the United States, um,

We don't have an easy way of regulating or legislating energy. Some of it is, of course, controlled by the states. Some of it is controlled at the federal level. The Trump administration is talking about making a lot easier to build. It's very, very important. And I do personally believe that we're going to need a portfolio approach.

We're going to need, yes, some natural gas. I hope that we finally get involved with nuclear because I think it could be done safely today. We're going to need to have wind. We're going to need to have solar, which are intermittent. So we're going to need to have battery storage in this country. But AI is global. So we will also build AI infrastructure in areas of the world where they have a surplus of energy. For example, the Middle East. And Trump just came back from his meetings over there and there were literally trillions of dollars pledged to build AI infrastructure. So I think this will be a global thing.

All of our research indicates that as you get to the later part of this decade, that certainly energy production could be an issue, a limiter to watch out for. But at least for the next two or three years, we're okay. Now, this is, of course, a global initiative with global impact. The U.S. is not the only show in town, and we've seen that this year with developments out of China and the impacts that has had to air markets here in the U.S. How do innovations here impact

in the U.S. thus far? How have they measured up to innovations we've seen come out of other countries, most notably this year, China? Yeah, early in the year, we did a webinar. So anybody can go to the Barron website, listen to our webinar. We have what we call a Barron Insight piece. We literally addressed deep seek, I think.

It was probably sometime in January. The U.S., since the Internet age, has been the leader of innovation. We have Silicon Valley for a reason. The Mag7, all of which are digital companies, are U.S.-based businesses for a reason. We are still the leader in AI. When you think about the companies that are leading the race towards AGI, Artificial General Intelligence, or ASI, Artificial Superintelligence,

I will not name them all, but OpenAI, Anthropic, XAI, Meta with their Lama. Those companies are all U.S.-based companies. I think...

There was a shock sometimes called the Sputnik moment, right? You heard that bandied about in January. Because I think the US, we do have a certain amount of arrogance and we thought we were so far ahead of the Chinese. And we realized we aren't so far ahead of them. But we are ahead of them. As we wrote in our piece, there was a lot of panic about Deep Sea, what it would do to the markets. Oh my God, look how efficient they are. Of course, if you believe what they say, it's now been tested.

And our main point was if you plot a line of AI developments, DeepSeek would have just fit on the line. There's a French company called Mistral. If these developments had come out of Mistral and not DeepSeek, I don't even think we would have noticed it. And the reason it spurred such attention and debate and fear –

Because we live in an age of social media today. And if you're on social media, what do you need? You need eyeballs. You need engagements. So you got to create some controversy or some fear. I do think we as a country need to look out for China. 1.3 billion people there. A lot of really smart people. They will be a competitor of ours. But I think we will lead.

And then, of course, one of the issues on AI, and I'll stop and you can ask a follow-up question, is certainly what's now going to happen with tariffs or trade restrictions and what the Trump administration, at least for the next three and a half year, does to make sure that U.S. remains the leader in the age of AI. Do you have a sense for how the current administration is investing or allocating resources into the further development and implementation of this technology? Yeah.

I mean, to be fair and not political, there are, of course, mixed signals. Sure. So there have been lots and lots of announcements of AI investments in U.S. technology, whether it's U.S. physical technology chips, whether it's U.S. models, whether it's used the service providers, what we call the hyperscalers.

Starlink is going to be in the United States. Of course, we have lots of commitments overseas. At the same time, we've restricted our technology today going to China, which is a massive market. And I personally believe we should be the leaders in that market. You'd rather have your adversary dependent upon your technology rather than building their own ecosystem of technology. So there are mixed signals there.

But I wrote about this in a Corrie letter and I do feel that when you listen really, really carefully to people in the administration, they do understand that we are in another industrial revolution, which I can explain. And it's the AI revolution or evolution, whatever term people want to use. It is the future of the world and there's no doubt. The United States, even if you're a MAGA person or not, we should be in the leadership in AI. It's important for us.

Now, as far as how investors can get involved, it sounds like there are many avenues out there, perhaps for the everyday investor, it seems overwhelming. What's some guidance in terms of how to get started, how to invest in this technology? What are some considerations there for investors to be mindful of? I mean, of course, you know, in a sense, I'll sell what we do. I think it's very hard for an individual investor to.

to become an expert in AI, understand all the layers of what they call the AI stack, semiconductors, data, models, applications, just by way of example, and to figure out who are going to be the sustainable leaders there. We've already seen in the kind of the first two and a half years of AI, so many different companies going from

the Wall Street AI winner category to the AI loser, and you've seen their stocks' incredible volatility. You've had some that are clear AI winners. But even like NVIDIA, which no one doubts is an AI winner, got hurt earlier this year when there was a fear of deep seek, a fear that, oh, could there be a digestion period in building out all of this AI infrastructure? So I think it's very hard to do as an individual. So I do think people should invest with

portfolio manager, a fund such as like we have at Barron Capital, or of course you could do an ETF that you think has a good diverse selection of companies that are participating in AI. That's the best way I think. Please ask me any follow-ups here.

So that with every opportunity, of course, has risk associated with it. What are some risks when it comes to investing in this technology at the moment to be mindful of? Anything on your radar? Yeah, of course. I mean, I think the number one risk, as we talked about even before we started the show, is just the pace. I've never seen such a pace of developments, such a pace of innovation, such massive change before.

that predicting the future is very, very difficult now. So of course, that's a risk anytime investment. When you're investing, you want to pick the winners. We still live in a technology age where, as we've seen, I think over the last 25 years, the winners take most. Most get confused and think the winners take all. And therefore, if there's a single competitor, they panic. No, no, no. The winners will take most. But you got to understand who the winners are,

why they'll be a winner, what their competitive advantages are. It's hard because things are moving so fast.

There's, there's, we are building a significant amount of infrastructure for AI today, both AI training of these models, you know, um, by open AI, by all the other players that I listed before. And now we are moving to inference. When you hear that word inference, that is simply us again, as consumers or as business people utilizing the AI application. And I'm more than happy to dig into what inference really, really means the generation of an intelligent token, um, to produce words, produce pictures.

produce an action that has to be generated. So we have all of that infrastructure being built. But there's a fear because anytime we've built infrastructure, even going back to the days of building, you know, out the, you know, the train system in the United States, you get to some point where there's maybe a pause in the infrastructure build out. So we've had those fears.

Every piece of research that we do today, it will keep going. And I could talk about as we switch from training to inference why we think that will be more of a steady build. There's, of course, regulatory risks. What do we do with all of people's data? Because AI is fed by data. And so there's personal data. There's public data. What will happen there? There are certainly geopolitical risks. Of course, we've seen them now with what's happened in Ukraine, war in the Middle East.

And geopolitical will blend into what I'll call legislative, regulatory, certain trade. You know, will U.S. companies be able to sell to China? If we don't, will China be able to build a massive ecosystem like they're doing today with electric cars and like they've done with lots of other products, basically dump them on the world's market for cheap and therefore some of the U.S. companies that you may love have a tough time competing?

So there are a lot of risks here. And in our research, in our work, you want to invest with as much certainty as you can. I have a whole team of, you know, over 10 people focusing on AI. And I will be honest that the level of certainty is lower than I wish it was.

So we are picking the companies that based on all of our research are definitely more likely than not the winners. And we could articulate those reasons. But you're not in an age of having high level of certainty just because we're moving so fast. But just the last thing. Sure. The opportunity.

is massive, like nothing we've ever seen before. Well, Mike, absolute pleasure. Thank you for spending some time with our listeners, our advisors, very generous with your time for sharing your knowledge. It sounds like a lot more knowledge to share. So at some point, it would be great to have you back and have a follow-up conversation. Great. Thank you for having me.

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