Bloomberg Audio Studios, Podcasts, Radio News. Welcome to Maren Talks Money, the podcast in which people who.
Know the markets explain the markets.
I am Meren Sumset Web and with me today is Kathy Would, CEO and CIO of investment management firm ARC Invest now ARC Invests.
I think many of you will know.
In disruptive and innovative technologies of all kinds, so we're going to talk about quite a few of those today, AI, robotics, cryptocurrencies, all this kind of thing. Kathy, Absolute pleasure to have you with us today in our London studio.
Welcome, thank you, Maren, very very happy to be here. Right, we have got a lot to cover.
Big ideas. There are a lot of big ideas out there.
That's where I want to start with the Big Idea.
So you've put out at the beginning of every year ago Big Ideas Report, where you talk about what's going on with a lot and this year one of the main idea in it was that there are this amazing convergence of different types of technology coming together to create a wave of tech innovation the likes of which we really haven't seen before, and the consequences is going to be enormous. So can we just talk through to get us started those technologies and the convergence that you're expecting.
Sure, So, there are fifteen different technologies and they're included in the five major innovation or five innovation platforms that are evolving today. So AI the chatch GPT moment really did awaken investors to know something's going on here. So AI, robotics, energy storage, blockchain technology, and multiomic technology. And you're right,
the fifteen technologies are converging. Two of the biggest trends out of this convergence have to do with AI applications, so embodied AI, the physical and the digital world coming together. So if we look at autonomous mobility, so robotaxis, that involves three of the major innovation platforms converging. So autonomous vehicles are robots, they will be electric, and they will be powered by AI.
So AI robotic energy storage.
Yes, and so if you think about those, those are three different s curves in the world of innovation slowly slowly than all at once, and they're beginning to feed each other. Tesla launched its robotaxi service in Austin in June, and we're seeing now a quickening of the pace. WEIMO is now moving more quickly into different cities. So there's a competitive dynamic that is going to accelerate the trend
towards robotaxis in the United States. And because robotaxis are safer, we've just crossed the human threshold of safety and will continue too.
That's true. That's true.
So that's one and we think that's the biggest application of AI from a revenue generation point of view, other than the productivity tools that we're using right now. We're already yes, absolutely, and we're paying for them and we're going to pay more and more because they are that useful. The second major trend is in healthcare. It's the most profound application of AI, and it includes the convergence of
sequencing technologies AI and Crisper gene editing. So sequencing, we have thirty five to forty trillion cells in our body generating data, and AI is a data project. Proprietary data is key to success. So sequencing technologies AI now that we can find mutations, which are programming errors in our body. We have six billion bits of code. If you think about three billion base pairs of DNA pairs, so six
billion bits of code. We can now see when one of them has gone awry, when there's been a mutation. Now and we can see it because of AI. We couldn't have done any of this five, ten, fifteen years ago. Now that we can see it, we can use Crisper gene editing to reprogram the genome. And we're already seeing cures for beta thalocemia and sickle cell disease, and we're seeing revenue generation. Crisper Therapeutics is the company and Vertex it's partner, generating revenues and curing disease.
Those are diseases.
We think these technologies will impact common diseases in the not too distant future.
And chrispre's one of your big holdings in the innovation ATIA it is it's I think it's.
Our number two holding.
It's earned it, yes, yes, yes, yes so. And one of the reasons it's up there is in its pipeline is a cure. Now it's in trials for bad cholesterol. Think about that. Cardiovascular disease is the biggest killer in the world. And what we're going to do here is shift sick care dollars. So just treating chronic disease shifting six sick care dollars or pounds or euros into really therapies that cure or prevent or into diagnostic tools that diagnose cancer in stage one or before stage one with
blood tests. So we think healthcare is going to transform completely.
Here, okay.
The idea there being that people will end up with a much not necessarily a much longer life, but a longer health span, a longer period of healthy living.
Yes, and we are writing a white paper about longevity. But you're absolutely right, maarn. The first order here is to extend healthy life, you know, increase the quality of life while we are alive.
Yeah, and if that happens, that is transformative for public finances apart from anything else. Right, So the end of life that last ten years is the most expensive bit for any healthcare system and hans for any government.
You can take that out suddenly. Possibly.
The fiscal situations of the Western economies don't.
Look quite awful.
Absolutely, And the US is the worst that way, because we spend nearly twenty percent of GDP on healthcare. I think in the UK it's less than ten percent.
Round eleven, but oh, you know, it's huge.
Okay, So it's huge and in the US there's a lot because of our litigiousness, there's a lot of unnecessary spending, and so we will get those answers, yes spend and no, don't spend.
Okay, So we have this convergence of these extraordinary technologies which gives us this acceleration in everything, right, acceleration and productivity, acceleration in GDP growth. I know you're very optimistic about growth across the board as a result.
Of all these innovations.
Yes, if you look in Big Ideas, you'll see there's a chart, a timeline, and it's in the section called the Great Acceleration. So our chief futurist, Brett Winton named his section the Great Acceleration, thinking people would understand that, no, we're not going into the Great Depression. We're going into the Great Acceleration. I have to explain that I've told him, because I didn't get so. Anyways, So the Great Acceleration.
If you look, you'll find a GDP chart, and the timeline is broken down by tech breakthroughs, you know, tech revolutions. So if you look in the years from fifteen hundred to nineteen hundred, nothing much changed. And as best as Brett could ascertain with you know, consulting, academia and so forth. Global real GDP growth in that time period was about
zero point six percent, so very slow. And then we have really the industrial revolution, first the railroads and then building on the railroads, we had telephone, electricity, and the internal combustion engine, and we had then a step function increase in growth to three percent real GDP growth globally for one hundred and twenty five years on average, with China joining in at the end. Now we believe with
these five innovation platforms. So there were three major ones on top of railroads, there are five major ones on top of the internet. The Internet was sort of the prelude, much like the railroads were. So five innovation platforms which involve fourteen i mean fifteen different technologies which we think are going to take growth into the seven to eight percent range. Now many people think that sounds ridiculous, but that's not. The last technology revolution, which we don't think
was as big as this one's going to be. We had a fivefold increase. We're saying maybe a two and a half fold increase, so we think we're being conservative. But the other thing to note is these technologies are deflationary. So if we were to enter this seven to eight percent growth range, it probably would be accompanied by deflation. And many people just don't believe that. But the deflation being caused by AI alone. AI training costs are dropping
seventy five percent per year. AI inference costs, So what it costs to deliver an answer to your query, those are dropping eighty five to if you believe deep seek ninety eight percent per year cost. This is technology. It's called learning curves. So the more units produced in this case tokens in the world of AI, the lower costs go.
It's the learning curves associated with technologies. So when a technology is mature, like the internal combustion engine autos, there isn't much unit growth, so the costs don't come down anymore. Right now, the unit growth in AI is exploding and therefore the cost and sort of the undertow, the deflationary undertoes we think are picking up here.
Now.
Of course, we have oil on the other side of this. We think this is temporary, better be temporary, right, and this deflation is being somewhat obfuscated, But there is a measure. It's in the blockchain world. It's called trueflation measures ten thousand items twenty four to seven.
I keep an eye on that, and it's alf very, very different to the official inflation numbers.
Yes, it was higher coming out of COVID. It got to eleven twelve percent, whereas the CPI in the US got to nine percent.
Now it's one and a half percent.
Whereas the inflation measures, especially with oil and tariffs, they're kind of sticky in this two to three percent range. Trueflation, we think is getting it right. It did drop below one percent, and now we've had a bit of a bounce because of energy prices.
But even if then the oil price rise is temporary, Even if the att least is sorted out and everything's fine, old Press falls back down again. Still one of the main limitations to a lot of this is energy, right, and we know how energy intensive anything to do with AI is, so that still remains one of the limitations absolutely.
And one of the limitations of course in the United States and elsewhere in the world is getting connected to the grid. It takes five years. So Elon has gotten very creative and brought in generators and batteries, and so he was able to get his Memphis data centers xais up in I think it was it was fewer than eight months, and most people thought it would take him years. Now he's thinking about data centers in space, and we're
doing that work. In fact, we have published our SpaceX model and anyone can go to our site or to get hub and find it and if they disagree with our assumptions, they can change them and see a different number, which SpaceX is going to go public, So this is going to become more important. We are adding in data centers that will be additive to the model, and we do think it's possible.
And if you have your data sense is in space, then they simply use solar energy solar and everything.
Is very straightforward, very straightforward.
And this brings into play reusable rockets that just go up and down lutely, and that's been the real breakthrough here.
Without reusable rockets, it would be prohibitively expensive to put satellites into space. SpaceX has about two thirds of the satellites in space right now, and other rocket providers are attempting the reusable rocket space, but SpaceX is ten years ahead.
Okay, So if we get to that point where most of the data centers are in space, and that takes away the energy limitation. It takes away the land limitation, the grid limitation.
All of the litory, the bureaucracy, there's no bureaucracy, takes away.
The regulatory I we know right now there is no bureaucracy or regulatory environment in space. But the more full space becomes, eventually there will have to be a regulatory regime around it.
Right yes, yes, at place who own space. We don't know doing.
Exactly that's that's going to be a company. I mean, it almost seems that this is a technology race, and that is why China is now racing to the moon and experimenting with reusable rockets as well. Okay, how far away do you think that is, by the way, before we move on, yes, orbital data centers, Yes, by our calculations, twenty thirty, twenty thirty one, So we still will be dealing with the bureaucracy and the regulation here. So yes, it's that time period is where we consider the energy drain.
The shift comes at first and last time we talked to Kathy when we talked about the energy limitations on AI.
We talked about nuclear energy and about how.
That was the solution that we've already pushed that to one side because it doesn't matter anymore because we're going to space.
What's interesting is the Trump administration recognizes that economic activity is energy transformed. Now, what has happened in the last fifteen twenty years was a movement towards more efficient energy use.
So that was good, and that.
Was very good, and we've become much more efficient. But now, because we believe GDP growth is going to accelerate, we need more more energy, and so nuclear absolutely is an answer. And I am shocked at the regulatory the speed of regulatory change in the United States. Now, what's interesting this is another race. China has about thirty nuclear plants big
ones being built today. The US has zero, and so this is shocking to those of us who believe that real GDP growth is going to accelerate and we need the energy to do so. So we're now seeing some approvals, but we're also seeing breakthroughs in small modular reactors, and of course open AI with OClO really started that movement. In the public equity markets. There is a lot more going on in the private equity markets.
It's interesting, isn't.
That how as you say, we've been through this phase where the drive behind everything has been to try and use less energy.
Yes, and that is not the way that wealthlies, isn't it. That's right.
I do think going through that period was important because there was a lot of waste and we have gotten a lot better. But now we're going to have to step up energy production of all in order to accommodate this new world.
Let's talk about the winners and the losers here, because it sounds like everything is becoming a little bit more clear. We have more of an idea of what the future is going to look like than maybe we did even a year or or two ago. As these things converge. But when you look at stock markets and listed companies, then you can now begin to.
See who m win and who might lose.
Yes, well, I have to start with Tesla. It's our largest position, at least in our flagship fund. Europe is really I think approaching ore and maybe it's because of your podcast, Mirion, but approaching our strategy in the correct way as a satellite strategy. So our largest position in the flagship strategy and in our AI and robotics strategy. I mean there's a bit of a competition there, but it's up there. It's Tesla because that is the largest AI project on Earth, and it embodies this idea of
the convergence among technologies. And in fact, Elon very recently kind of giving us a clue that he was going to combine SpaceX and XAI. He said, you know, my companies are going to converge more than I ever thought. And we thought that was a victory for us because we've been using this word convergence for a while, and
we've been describing Tesla in this way. And ultimately it could be that Tesla, XAI and SpaceX do get together, but we don't think yet, because I do think Elon wants to reward those of us who have been patient shareholders with the robotaxi takeoff, and now that analysts are being forced to look at this new world, they are seeing Tesla's model shift from sixteen percent gross margins in electric vehicles to ultimately with robotaxis just that opportunity segmented,
that's eighty to ninety percent gross margins.
It's a very competitive market, isn't it.
It seems so there are a lot of companies trying to enter. We do think This is a winner take most market because the company to get passengers from point A to point B the safest, the fastest, and the least expensively. And that last one is where Tesla will ultimately win, will win the lion's share. It's a little bit like Uber and Lyft. There's a network effect, and
so we think Tesla will win the lion's share. So if we're right, then globally, the revenue generation from autonomous taxis is going to skip globally, including China, is going to scale to north of ten trillion within the next five to ten years, and we're talking about only a billion dollars right now. And again, lions share will go to a few companies. The platform providers will get most of the profits. Tesla's a platform provider. Weimo is as well,
but Tesla because it's vertically integrated. From a manufacturing point of view, we believe that by twenty thirty its costs will be fifty percent lower than Weimo's costs given what we know now, and so it will be able to pass those lower costs on and provide a less expensive ride. And then, of course China is where a lot of other companies are evolving so buydos Apollo, Pony AI we ride, and then of course Uber is partnering with a lot of auto manufacturers.
Here in the UK, you have Wave.
We had the pleasure yesterday of taking a ride in Wave, and I have to tell you I was truly impressed, very impressed. And you know we've been we cut our teeth on cyber Cab and way Mow and so forth. So here in London, the streets being as complicated as they are and pedestrians all over the place. I was truly impressed. And it is partnering with all the OEMs because there's a sense of urgency now. They all pulled away during COVID from these investments in the future, and
now they realize they should not have done that. So now they're scrambling and Wave seems to be in the cat bird seat.
Okay.
Interesting and when is across the AI space, you know we've moved We've moved slightly on from the days of Mega seven, haven't we, And we sold all the disruption in the software space, etc.
It's becoming more obvious.
That not everyone's going to win in and this has been a wake up call. So we noted from our big ideas that if you split the tech stack into its three major components. So infrastructure, so that's data centers, chips and so forth. Platform as a service, which is really customized software often generated internally, but now pallentteer is turbocharging the customization of company data and company ontology. You know, every company has its own language, so that's in the middle.
And then the third was applications, so infrastructure, platform as a service, applications, and we saw all of them growing very nicely over the past five years. But when you do the second derivative, we learned that wait a minute, platform as a service is capturing much more the incremental growth than applications. What's going on here It was that
it was the SaaS copolps. It is palenteer and all of these customization efforts that are possible with AI now is taking share from sas, which is one size fits all, and so that was an important clue to us. So we did pull away in recognition, not understanding that there would be SaaS copolps, but just that there would be more opportunity in the platform and the infrastructure part of the tech stack.
Some of that was a surprise to other people.
Yes, when you look ahead, Now, what is the thing that you're most uncertain about that you look at? Because we've talked a lot about what you can see and what you can expect. What is it that you look at and then well, I just don't know how that's going to unfold. What are the big unknowns in these factors?
Well, I think the most important question for us, thank you, is unit growth. What would impede the unit growth of these technologies? And we learned an important lesson in COVID. We had no idea that there would be that this supply shock would cause supply chain issues for three years, and that did slow down a lot of our technologies. So we learned an important lesson there anything, whether it's
geopolitical risk. And sure, we have this Iran war and the question coming out of it is, oh, my gosh, is this another supply shock that's going to cause another few years? We don't think so, but it is the right question. One of the reasons we don't think so is what did we learn from COVID. We learned that just in time, so jit manufacturing had gone too far.
We need buffers, So we need just in case. And I think that That's what we have done during the last few years, is we've started building in those buffers. But that's the most important unknown to us.
And I suppose the other thing is that we're talking about supply crunches is the possibility of supply problems with that rare metals and various commodities, not just oil, right, yes, just about fossil fields.
Yes, And I do think that President Trump, in his negotiations with President Jijiping, is focused on this quid pro quo.
We have the oil that they.
Need, especially if Iran and others energy is shut down in some way. I think China gets eighty percent of whatever flows through the Straits of Hormuz, right, so.
We can be that fallback.
They need to give their rare earths, and we in the United States need to deregulate. Why don't we have rare earths because in nineteen eighty our regulators decided that any waste from rare earths should be treated like nuclear waste. So everyone stopped. That is changing, yes, changing, yes, changing, yeah, yes.
Well, at that brings me to the other limitation that you might find around pretty much everything, which of course is regulation. Yes, and you know, increasingly the whole conversation around AI gets quite.
Emotional, doesn't that.
Yes, And if you look on social media, you'll see these stories playing out of these terrible end games, one of them of course being mass unemployment, etc. So is there a concern that the regulatory build up around the use of AI might turn into a headwind.
Well, in the United States, there was a regulatory build up. There was an executive order which President Trump rescinded first thing, and now we're seeing in New York ridiculous legislation, so you know, being proposed saying no corporation can use large language models. It's like, that's crazy. If New York wants to continue the exodus from New York to my state of Florida or Texas or other more business friendly, capital friendly states, that's the way to do that. That's the
way to do it. And I think this mass unemployment that is it is the unions who are behind this legislation. Mass unemployment, I think is exaggerated. There will be displacement, and in fact, already we're seeing in the cohort sixteen to twenty four years old, that unemployment rate is going up. It's at nine and a half percent in the US versus four point four for the overall unemployment rate. So those entry level jobs, those are disappearing and giving way
to AI. What's happening in the US, though, interestingly, is despite what we just heard from Metaplatform laying off twenty percent of its workforce to afford the capital spending, we are seeing more people holding their jobs. They're they're not layoffs, and so we're already starting to see entry level jobs disappearing. But those who are at work are taking up that
challenge and saying, I'll run with this AI. I know in our firm everyone's really excited about what we can do, and in fact, everyone's asking for bigger budgets so they can do more. So I think the saying goes that those who lose their jobs will it won't be because of AI. It will because be because of someone else using AI and becoming much more productive. So that's a clarion call for everyone to just, you know, really delve into this opportunity. It is a huge opportunity for everyone
to increase productivity. And we you know the history of technology is net job creation.
Long term.
Sure, short term.
Some iceplace out with a lost generation along the way.
Yes, well, but they have an opportunity. You know what's so wonderful about this AI opportunity or technology opportunity.
This isn't going.
To coders and developers. Sure the developers, the most productive ones are benefiting. It's going to almost anyone. If you speak a natural language, you can vibe what's called vibcode, vibe code with chat, GBT or claud and start your own business, solve a problem that you see out there. And I'm counseling young people especially to do that because maybe it takes six months on average to find a job if you're unemployed in the US, the median is
three months. But if you look for the job, but in the meantime try and start your own business using AI, you're going to be become much more attractive to employers out there, anyone with AI initiative. And again this is all natural language, so it's about initiative, not girl exactly exactly, and creativity and imagination.
Speaking of which, the big IPAs that everyone is talking about SpaceX anthropic open AI. Are you still expecting those this year or do you think maybe the Middle East, etcetera.
Will have pushed it out a bit.
I think the reason we'll see more this year than otherwise might have been the case is because of the midterm elections. If the Republicans lose the House, it could be that will be in a more stringent regulatory environment.
Yes, they might come forward, right right, right. Interesting. Let me then connect with question evaluations.
Now, one of the things that is often talked about, of course, is the high valuations, and of course lots of the companies that you invest in. Yes, and I suspect that your view, obviously is that your companies will grow in to that valuations. The other view, of course, is that they will collapse into that that valuation, into the correct valuation.
Yes, yes, it's a very good contrast to help me explain what we're doing. Yes, our companies do sell at premium multiples. Why because we want them to sacrifice short term profitability and invest aggressively to capitalize on these really
massive opportunities. So, while they do have premium multiples right now, our assumption is that that valuation will compress to a market multiple during the next five years, and our analysts and portfolio managers must believe that the revenue growth and margin expansion is going to overwhelm that headwind, and you're right, grow into the valuations is another way of saying it.
But to visualize it mathematically, we're saying, no, that is a big headwind for the next five years, and our analyst and portfolio managers must believe that revenue growth, margin expansion will overwhelm the valuation compression and deliver a minimum hurdle rate of return of fifteen percent at a compound any rate during the next five years.
Okay, and if that happens, everything really is fine. Yes, yes, yes, yes, Okay.
Let me ask you one last question because our listeners will not forgive me if I do not bitcoin. The one thing we haven't talked about is the monetary system and possible changes within.
Are you still fully confident in your view here? Yes, on bitcoin. Absolutely. Bitcoin we believe is going to be the most important crypto asset for three reasons. It's really three big ideas in one. The first is it's a new technology. We have now currency native to the Internet, which is going to take out a lot of friction from the buying process, especially as we move to agentic AI, where you know, machines will be will be buying from
other machines. Right, So that's the first thing. The second is it is a global monetary system and we're beginning to see it react to the events in the Middle East, and it has stabilized after something called a flash crash from last October which caused autod leveraging, which caught a lot of people off sides. We think that's all washed through. We think Iran now is taking center stage and that Bitcoin will serve its role as a store of value.
We just hit twenty million bitcoin minted ever and we're going only to twenty one million gold. With the increase in price, I guarantee you miners have accelerated their search for more gold and will be producing more. Bitcoin is mathematically metered and its growth rate has already slipped below that of gold. And we also think with the huge intergenerational wealth transfer taking place, that bitcoin will be the
store of value of choice. And then the third big idea is bitcoin and we wrote this paper in twenty sixteen. I'm very proud of our team. Bitcoin the first of its kind in a new asset class. If you look at bitcoin, it's correlation relative to other assets is very low, even to gold. Many we call it digital gold.
But if you look at.
The correlation since twenty nineteen, really since institutions started thinking about this. The correlation between gold and bitcoin is zero point one four, hardly any correlation. And if you look at a matrix I put it in my New Year's letter in January, we have a matrix you'll see the correlation with other assets is very low.
So what does this mean?
Acid allocators are looking for low correlation assets because if they in the satellite strategy that we offer, if they put a lower correlation asset in their mix, their risk adjusted returns go up over time.
So maybe everyone should just hold bitcoin and gold and be done with it if you want a store of value.
Yes, Kathy, thank you very much for joining yesterday.
Really appreciate it.
Thank you very much.
Thanks for listening to this week's Merin Talks Money.
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